1785:(3-SSIM) is a form of SSIM that takes into account the fact that the human eye can see differences more precisely on textured or edge regions than on smooth regions. The resulting metric is calculated as a weighted average of SSIM for three categories of regions: edges, textures, and smooth regions. The proposed weighting is 0.5 for edges, 0.25 for the textured and smooth regions. The authors mention that a 1/0/0 weighting (ignoring anything but edge distortions) leads to results that are closer to subjective ratings. This suggests that edge regions play a dominant role in image quality perception.
1758:) values. The resultant SSIM index is a decimal value between -1 and 1, where 1 indicates perfect similarity, 0 indicates no similarity, and -1 indicates perfect anti-correlation. For an image, it is typically calculated using a sliding Gaussian window of size 11x11 or a block window of size 8Ă—8. The window can be displaced pixel-by-pixel on the image to create an SSIM quality map of the image. In the case of video quality assessment, the authors propose to use only a subgroup of the possible windows to reduce the complexity of the calculation.
75:. Structural information is the idea that the pixels have strong inter-dependencies especially when they are spatially close. These dependencies carry important information about the structure of the objects in the visual scene. Luminance masking is a phenomenon whereby image distortions (in this context) tend to be less visible in bright regions, while contrast masking is a phenomenon whereby distortions become less visible where there is significant activity or "texture" in the image.
2351:
1905:
2786:
found to correlate as well as MSE-based methods on subjective databases other than the databases from SSIM's creators. As an example, they cite
Reibman and Poole, who found that MSE outperformed SSIM on a database containing packet-loss–impaired video. In another paper, an analytical link between PSNR and SSIM was identified.
449:
2785:
A paper by
Dosselmann and Yang claims that the performance of SSIM is "much closer to that of the MSE" than usually assumed. While they do not dispute the advantage of SSIM over MSE, they state an analytical and functional dependency between the two metrics. According to their research, SSIM has been
1771:
A more advanced form of SSIM, called
Multiscale SSIM (MS-SSIM) is conducted over multiple scales through a process of multiple stages of sub-sampling, reminiscent of multiscale processing in the early vision system. It has been shown to perform equally well or better than SSIM on different subjective
1899:
The complex wavelet transform variant of the SSIM (CW-SSIM) is designed to deal with issues of image scaling, translation and rotation. Instead of giving low scores to images with such conditions, the CW-SSIM takes advantage of the complex wavelet transform and therefore yields higher scores to said
1890:
It is worth noting that the original version SSIM was designed to measure the quality of still images. It does not contain any parameters directly related to temporal effects of human perception and human judgment. A common practice is to calculate the average SSIM value over all frames in the video
2764:
is the original image we wish to recover. The traditional filter which is used to solve this problem is the Wiener Filter. However, the Wiener filter design is based on the MSE. Using an SSIM variant, specifically Stat-SSIM, is claimed to produce better visual results, according to the algorithm's
2478:
The SSIMPLUS index is based on SSIM and is a commercially available tool. It extends SSIM's capabilities, mainly to target video applications. It provides scores in the range of 0–100, linearly matched to human subjective ratings. It also allows adapting the scores to the intended viewing device,
2469:
is a small positive number used for the purposes of function stability. Ideally, it should be zero. Like the SSIM, the CW-SSIM has a maximum value of 1. The maximum value of 1 indicates that the two signals are perfectly structurally similar while a value of 0 indicates no structural similarity.
2768:
Pattern
Recognition: Since SSIM mimics aspects of human perception, it could be used for recognizing patterns. When faced with issues like image scaling, translation and rotation, the algorithm's authors claim that it is better to use CW-SSIM, which is insensitive to these variations and may be
3508:
Prieto, Gabriel; Guibelalde, Eduardo; Chevalier, Margarita; Turrero, AgustĂn (21 July 2011). "Use of the cross-correlation component of the multiscale structural similarity metric (R* metric) for the evaluation of medical images: R* metric for the evaluation of medical images".
105:. In addition to defining the SSIM quality index, the paper provides a general context for developing and evaluating perceptual quality measures, including connections to human visual neurobiology and perception, and direct validation of the index against human subject ratings.
2346:{\displaystyle {\text{CW-SSIM}}(c_{x},c_{y})={\bigg (}{\frac {2\sum _{i=1}^{N}|c_{x,i}||c_{y,i}|+K}{\sum _{i=1}^{N}|c_{x,i}|^{2}+\sum _{i=1}^{N}|c_{y,i}|^{2}+K}}{\bigg )}{\bigg (}{\frac {2|\sum _{i=1}^{N}c_{x,i}c_{y,i}^{*}|+K}{2\sum _{i=1}^{N}|c_{x,i}c_{y,i}^{*}|+K}}{\bigg )}}
2769:
directly applied by template matching without using any training sample. Since data-driven pattern recognition approaches may produce better performance when a large amount of data is available for training, the authors suggest using CW-SSIM in data-driven approaches.
2639:, information is deliberately discarded to decrease the storage space of images and video. The MSE is typically used in such compression schemes. According to its authors, using SSIM instead of MSE is suggested to produce better results for the decompressed images.
135:
Sustained Impact Award for 2016, indicative of a paper having an unusually high impact for at least 10 years following its publication. Because of its high adoption by the television industry, the authors of the original SSIM paper were each accorded a
223:
1401:
2482:
According to its authors, SSIMPLUS achieves higher accuracy and higher speed than other image and video quality metrics. However, no independent evaluation of SSIMPLUS has been performed, as the algorithm itself is not publicly available.
1686:
48:) is a method for predicting the perceived quality of digital television and cinematic pictures, as well as other kinds of digital images and videos. It is also used for measuring the similarity between two images. The SSIM index is a
1272:
1507:
1881:
2519:
color space and combine MS-SSIM with two types of asymmetric error maps for blockiness/ringing and smoothing/blur, common compression artifacts. SSIMULACRA2 is part of libjxl, the reference implementation of
2622:
The modifications above can be combined. For example, 4-G-r* is a combination of 4-SSIM, G-SSIM, and r*. It is able to reflect radiologist preference for images much better than other SSIM variants tested.
4051:
1734:. However, under certain conditions, SSIM may be converted to a normalized root MSE measure, which is a distance function. The square of such a function is not convex, but is locally convex and
123:
SSIM subsequently found strong adoption in the image processing community and in the television and social media industries. The 2004 SSIM paper has been cited over 50,000 times according to
1278:
965:
1720:
864:
808:
1149:
650:
592:
1560:
706:
4044:
1033:
1000:
216:
1407:
534:
481:
2682:
1802:
Structural dissimilarity (DSSIM) may be derived from SSIM, though it does not constitute a distance function as the triangle inequality is not necessarily satisfied.
63:, while also incorporating important perceptual phenomena, including both luminance masking and contrast masking terms. The difference with other techniques such as
1794:(4-SSIM). The edge types are further subdivided into preserved and changed edges by their distortion status. The proposed weighting is 0.25 for all four components.
444:{\displaystyle {\hbox{SSIM}}(x,y)={\frac {(2\mu _{x}\mu _{y}+c_{1})(2\sigma _{xy}+c_{2})}{(\mu _{x}^{2}+\mu _{y}^{2}+c_{1})(\sigma _{x}^{2}+\sigma _{y}^{2}+c_{2})}}}
2427:
2380:
1570:
2762:
2742:
2722:
2702:
2467:
2447:
2400:
1142:
1122:
1102:
1082:
1062:
886:
750:
730:
674:
616:
558:
505:
190:
170:
4037:
1807:
3999:
4087:
141:
2778:
Due to its popularity, SSIM is often compared to other metrics, including more simple metrics such as MSE and PSNR, and other perceptual image and
3585:
Renieblas, Gabriel Prieto; NoguĂ©s, AgustĂn
Turrero; González, Alberto Muñoz; Gómez-Leon, Nieves; del Castillo, Eduardo Guibelalde (26 July 2017).
3490:
2830:
Wang, Zhou; Bovik, A.C.; Sheikh, H.R.; Simoncelli, E.P. (2004-04-01). "Image quality assessment: from error visibility to structural similarity".
2782:. SSIM has been repeatedly shown to significantly outperform MSE and its derivates in accuracy, including research by its own authors and others.
3657:
Zhang, Lin; Zhang, Lei; Mou, X.; Zhang, D. (September 2012). "A comprehensive evaluation of full reference image quality assessment algorithms".
3957:
3916:
3786:
3684:
2974:
1730:
SSIM satisfies the identity of indiscernibles, and symmetry properties, but not the triangle inequality or non-negativity, and thus is not a
101:
2899:
2805:
2500:
4185:
4180:
3561:
3544:
Chen, Guan-hao; Yang, Chun-ling; Xie, Sheng-li (October 2006). "Gradient-Based
Structural Similarity for Image Quality Assessment".
109:
4019:
3109:
137:
3196:
Li, Chaofeng; Bovik, Alan Conrad (2010-01-01). "Content-weighted video quality assessment using a three-component image model".
4407:
4268:
4092:
132:
128:
127:, making it one of the highest cited papers in the image processing and video engineering fields. It was recognized with the
3239:
Li, Chaofeng; Bovik, Alan C. (August 2010). "Content-partitioned structural similarity index for image quality assessment".
4358:
4102:
3349:
Zhou Wang; Bovik, A.C. (January 2009). "Mean squared error: Love it or leave it? A new look at Signal
Fidelity Measures".
4117:
3400:
Rehman, A.; Zeng, K.; Wang, Zhou (February 2015). Rogowitz, Bernice E; Pappas, Thrasyvoulos N; De Ridder, Huib (eds.).
2947:
Wang, Z.; Simoncelli, E.P.; Bovik, A.C. (2003-11-01). "Multiscale structural similarity for image quality assessment".
4324:
4253:
4190:
3839:"Maximum differentiation (MAD) competition: a methodology for comparing computational models of perceptual quantities"
3759:
Channappayya, S. S.; Bovik, A. C.; Caramanis, C.; Heath, R. W. (March 2008). "SSIM-optimal linear image restoration".
3708:
Zhou Wang; Wang, Zhou; Li, Qiang (May 2011). "Information
Content Weighting for Perceptual Image Quality Assessment".
3108:
Søgaard, Jacob; Krasula, Lukáš; Shahid, Muhammad; Temel, Dogancan; Brunnström, Kjell; Razaak, Manzoor (2016-02-14).
4137:
4112:
4097:
3451:
3153:
Dosselmann, Richard; Yang, Xue Dong (2009-11-06). "A comprehensive assessment of the structural similarity index".
2800:
68:
4441:
4127:
4122:
4223:
2643:
895:
3810:
Gore, Akshay; Gupta, Savita (2015-02-01). "Full reference image quality metrics for JPEG compressed images".
3002:
4314:
4218:
4213:
1693:
4381:
4155:
3894:
3889:
Reibman, A. R.; Poole, D. (September 2007). "Characterizing packet-loss impairments in compressed video".
3764:
3662:
3308:
3075:
2952:
2847:
117:
813:
757:
31:
2923:
537:
484:
3266:
4376:
4276:
4165:
4160:
3717:
3416:
3358:
3300:
3205:
3017:
2839:
1396:{\displaystyle c(x,y)={\frac {2\sigma _{x}\sigma _{y}+c_{2}}{\sigma _{x}^{2}+\sigma _{y}^{2}+c_{2}}}}
623:
565:
3899:
3769:
3667:
3313:
116:. Further variants of the model have been developed in the Image and Visual Computing Laboratory at
4082:
4069:
4024:
2957:
1517:
113:
3080:
2852:
681:
4402:
4368:
4248:
4077:
3963:
3922:
3792:
3741:
3690:
3567:
3432:
3382:
3178:
3132:
3041:
2980:
2881:
2795:
2612:
when only one is zero. It has found use in analyzing human response to contrast-detail phantoms.
64:
3110:"Applicability of Existing Objective Metrics of Perceptual Quality for Adaptive Video Streaming"
1005:
972:
195:
4397:
4286:
4233:
3953:
3912:
3871:
3782:
3733:
3680:
3616:
3557:
3526:
3374:
3326:
3221:
3170:
3033:
2970:
2873:
2865:
2636:
1731:
1681:{\displaystyle {\text{SSIM}}(x,y)=l(x,y)^{\alpha }\cdot c(x,y)^{\beta }\cdot s(x,y)^{\gamma }}
512:
459:
3638:
2649:
152:
The SSIM index is calculated on various windows of an image. The measure between two windows
4420:
4205:
4170:
4107:
4060:
3945:
3904:
3861:
3853:
3819:
3774:
3725:
3672:
3606:
3598:
3549:
3518:
3424:
3401:
3366:
3318:
3285:
3248:
3213:
3162:
3128:
3124:
3085:
3063:
3025:
2962:
2857:
2405:
2358:
4353:
4296:
4175:
2532:
The r* cross-correlation metric is based on the variance metrics of SSIM. It's defined as
1751:
108:
The basic model was developed in the
Laboratory for Image and Video Engineering (LIVE) at
96:
3838:
1267:{\displaystyle l(x,y)={\frac {2\mu _{x}\mu _{y}+c_{1}}{\mu _{x}^{2}+\mu _{y}^{2}+c_{1}}}}
3721:
3587:"Structural similarity index family for image quality assessment in radiological images"
3477:"SSIMULACRA 2 - Structural SIMilarity Unveiling Local And Compression Related Artifacts"
3420:
3362:
3304:
3209:
3021:
2843:
3866:
3611:
3586:
2747:
2727:
2707:
2687:
2452:
2432:
2385:
1127:
1107:
1087:
1067:
1047:
871:
735:
715:
659:
601:
543:
490:
175:
155:
124:
4029:
3089:
4435:
4238:
4195:
4004:
3491:"Detecting the psychovisual impact of compression related artifacts using SSIMULACRA"
3452:"Convergence rate in terms of the continuous SSIM (cSSIM) index in RBF interpolation"
3286:"Video quality assessment using a statistical model of human visual speed perception"
2885:
2810:
2779:
889:
53:
49:
3796:
3694:
3571:
3182:
3136:
3045:
2984:
112:
and further developed jointly with the
Laboratory for Computational Vision (LCV) at
3984:
3967:
3926:
3436:
3386:
1747:
3745:
1044:
The SSIM formula is based on three comparison measurements between the samples of
1502:{\displaystyle s(x,y)={\frac {\sigma _{xy}+c_{3}}{\sigma _{x}\sigma _{y}+c_{3}}}}
3778:
3252:
2949:
The Thirty-Seventh Asilomar Conference on Signals, Systems & Computers, 2003
1746:
In order to evaluate the image quality, this formula is usually applied only on
1735:
3823:
2966:
4332:
4243:
4228:
4025:"Mystery Behind Similarity Measures MSE and SSIM", Gintautas Palubinskas, 2014
3908:
3676:
3166:
2631:
SSIM has applications in a variety of different problems. Some examples are:
2619:
of images, making it "G-SSIM". G-SSIM is especially useful on blurred images.
2512:
709:
92:
3761:
2008 IEEE International Conference on Acoustics, Speech and Signal Processing
3729:
3602:
3553:
3378:
3225:
3174:
3029:
2869:
99:, into the current version of SSIM, which was published in April 2004 in the
4150:
3476:
3370:
3322:
2861:
2515:
with the goal of fitted to subjective opinion data. The variants operate in
3875:
3737:
3620:
3530:
3330:
3037:
2877:
56:
is based on an initial uncompressed or distortion-free image as reference.
3949:
3940:
Hore, A.; Ziou, D. (August 2010). "Image Quality Metrics: PSNR vs. SSIM".
1891:
sequence. However, several temporal variants of SSIM have been developed.
2616:
653:
595:
95:
in 2001. This evolved, through their collaboration with Hamid Sheikh and
3409:
IS&T-SPIE Electronic Imaging, Human Vision and Electronic Imaging XX
4258:
4145:
3428:
2521:
3522:
3217:
3064:"Video quality assessment based on structural distortion measurement"
1876:{\displaystyle {\hbox{DSSIM}}(x,y)={\frac {1-{\hbox{SSIM}}(x,y)}{2}}}
59:
SSIM is a perception-based model that considers image degradation as
17:
3994:
3857:
3003:"On the mathematical properties of the structural similarity index"
1565:
SSIM is then a weighted combination of those comparative measures:
3989:
1755:
4337:
4309:
4304:
4281:
4033:
3402:"Display device-adapted video quality-of-experience assessment"
2499:
SSIM (cSSIM) has been introduced and studied in the context of
2516:
866:
two variables to stabilize the division with weak denominator;
3812:
AEU - International Journal of Electronics and Communications
3646:. IEEE International Conference on Image Processing (ICIP11).
2511:
SSIMULACRA and SSIMULACRA2 are variants of SSIM developed by
4014:
4009:
3001:
Brunet, D.; Vass, J.; Vrscay, E. R.; Wang, Z. (April 2012).
3659:
2012 19th IEEE International Conference on Image Processing
3057:
3055:
2479:
comparing video across different resolutions and contents.
1722:
to 1, the formula can be reduced to the form shown above.
3942:
2010 20th International Conference on Pattern Recognition
1788:
The authors of 3-SSIM have also extended the model into
3891:
2007 IEEE International Conference on Image Processing
1846:
1812:
228:
2750:
2730:
2710:
2690:
2652:
2455:
2435:
2408:
2388:
2361:
1908:
1810:
1696:
1573:
1520:
1410:
1281:
1152:
1130:
1110:
1090:
1070:
1050:
1008:
975:
898:
874:
816:
760:
738:
718:
684:
662:
626:
604:
568:
546:
515:
493:
462:
226:
198:
178:
158:
4390:
4367:
4346:
4323:
4295:
4267:
4204:
4136:
4068:
52:; in other words, the measurement or prediction of
2924:"IEEE Signal Processing Society, Best Paper Award"
2756:
2736:
2716:
2696:
2676:
2461:
2441:
2421:
2394:
2374:
2345:
1875:
1750:, although it may also be applied on color (e.g.,
1738:, making SSIM a feasible target for optimization.
1714:
1680:
1554:
1501:
1395:
1266:
1136:
1116:
1096:
1076:
1056:
1027:
994:
959:
880:
858:
802:
744:
724:
700:
668:
644:
610:
586:
552:
528:
499:
475:
443:
210:
184:
164:
3546:2006 International Conference on Image Processing
2338:
2169:
2162:
1948:
3637:Gao, Y.; Rehman, A.; Wang, Z. (September 2011).
3062:Wang, Z.; Lu, L.; Bovik, A. C. (February 2004).
2996:
2994:
2429:is the complex wavelet transform for the signal
131:Best Paper Award for 2009. It also received the
2382:is the complex wavelet transform of the signal
3837:Wang, Z.; Simoncelli, E. P. (September 2008).
4045:
2704:is the blurry image that should be restored,
2491:In order to further investigate the standard
8:
2608:when both standard deviations are zero, and
1144:). The individual comparison functions are:
3632:
3630:
3293:Journal of the Optical Society of America A
1900:images. The CW-SSIM is defined as follows:
1886:Video quality metrics and temporal variants
30:"SSIM" redirects here. For other uses, see
4052:
4038:
4030:
3411:. Human Vision and Electronic Imaging XX.
2806:Video Multimethod Assessment Fusion (VMAF)
61:perceived change in structural information
4010:qpsnr implementation (multi threaded C++)
3898:
3865:
3768:
3666:
3610:
3312:
3079:
2956:
2951:. Vol. 2. pp. 1398–1402 Vol.2.
2851:
2749:
2729:
2709:
2689:
2651:
2495:SSIM from a theoretical perspective, the
2454:
2434:
2413:
2407:
2387:
2366:
2360:
2337:
2336:
2322:
2316:
2305:
2289:
2280:
2274:
2263:
2243:
2237:
2226:
2210:
2200:
2189:
2180:
2174:
2168:
2167:
2161:
2160:
2145:
2140:
2127:
2118:
2112:
2101:
2088:
2083:
2070:
2061:
2055:
2044:
2027:
2015:
2006:
2001:
1989:
1980:
1974:
1963:
1953:
1947:
1946:
1934:
1921:
1909:
1907:
1845:
1836:
1811:
1809:
1695:
1672:
1644:
1616:
1574:
1572:
1544:
1538:
1525:
1519:
1511:with, in addition to above definitions:
1490:
1477:
1467:
1455:
1439:
1432:
1409:
1384:
1371:
1366:
1353:
1348:
1336:
1323:
1313:
1303:
1280:
1255:
1242:
1237:
1224:
1219:
1207:
1194:
1184:
1174:
1151:
1129:
1109:
1089:
1069:
1049:
1013:
1007:
980:
974:
903:
897:
873:
850:
837:
821:
815:
794:
781:
765:
759:
737:
717:
689:
683:
661:
636:
631:
625:
603:
578:
573:
567:
545:
520:
514:
492:
467:
461:
429:
416:
411:
398:
393:
377:
364:
359:
346:
341:
323:
307:
288:
275:
265:
252:
227:
225:
197:
177:
157:
960:{\displaystyle 2^{\#bits\ per\ pixel}-1}
3893:. Vol. 5. pp. V – 77–V – 80.
3344:
3342:
3340:
3129:10.2352/issn.2470-1173.2016.13.iqsp-206
2822:
892:of the pixel-values (typically this is
91:, which was developed by Zhou Wang and
3241:Signal Processing: Image Communication
3068:Signal Processing: Image Communication
1715:{\displaystyle \alpha ,\beta ,\gamma }
3710:IEEE Transactions on Image Processing
3010:IEEE Transactions on Image Processing
2832:IEEE Transactions on Image Processing
120:and have been commercially marketed.
102:IEEE Transactions on Image Processing
7:
3148:
3146:
3103:
3101:
3099:
2942:
2940:
2938:
2936:
2501:Radial basis function interpolation
83:The predecessor of SSIM was called
27:Prediction of digital video quality
3640:CW-SSIM based image classification
3284:Wang, Z.; Li, Q. (December 2007).
3155:Signal, Image and Video Processing
904:
859:{\displaystyle c_{2}=(k_{2}L)^{2}}
803:{\displaystyle c_{1}=(k_{1}L)^{2}}
71:is that these approaches estimate
25:
110:The University of Texas at Austin
4005:Chris Lomont's C# Implementation
138:Primetime Engineering Emmy Award
4408:Pearson correlation coefficient
4015:Implementation in VQMT software
3351:IEEE Signal Processing Magazine
2646:focuses on solving the problem
2615:SSIM has also been used on the
645:{\displaystyle \sigma _{y}^{2}}
587:{\displaystyle \sigma _{x}^{2}}
3450:Marchetti, F. (January 2021).
2323:
2281:
2244:
2181:
2141:
2119:
2084:
2062:
2028:
2007:
2002:
1981:
1940:
1914:
1864:
1852:
1830:
1818:
1669:
1656:
1641:
1628:
1613:
1600:
1591:
1579:
1426:
1414:
1297:
1285:
1168:
1156:
847:
830:
791:
774:
435:
386:
383:
334:
329:
297:
294:
255:
246:
234:
133:IEEE Signal Processing Society
129:IEEE Signal Processing Society
1:
4347:Deep Learning Related Metrics
3198:Journal of Electronic Imaging
3090:10.1016/S0923-5965(03)00076-6
1555:{\displaystyle c_{3}=c_{2}/2}
2635:Image Compression: In lossy
1754:) values or chromatic (e.g.
701:{\displaystyle \sigma _{xy}}
4191:Sensitivity and specificity
3779:10.1109/icassp.2008.4517722
3479:. Cloudinary. 12 July 2023.
3253:10.1016/j.image.2010.03.004
1772:image and video databases.
4458:
3824:10.1016/j.aeue.2014.09.002
3591:Journal of Medical Imaging
2967:10.1109/ACSSC.2003.1292216
2801:Peak signal-to-noise ratio
2744:is the additive noise and
2528:Other simple modifications
1742:Application of the formula
1028:{\displaystyle k_{2}=0.03}
995:{\displaystyle k_{1}=0.01}
29:
4416:
3909:10.1109/icip.2007.4379769
3677:10.1109/icip.2012.6467150
3167:10.1007/s11760-009-0144-1
211:{\displaystyle N\times N}
4020:Implementation in Python
4000:DSSIM C++ Implementation
3730:10.1109/tip.2010.2092435
3603:10.1117/1.JMI.4.3.035501
3554:10.1109/ICIP.2006.313132
3459:Dolom. Res. Notes Approx
3030:10.1109/TIP.2011.2173206
1798:Structural Dissimilarity
529:{\displaystyle \mu _{y}}
476:{\displaystyle \mu _{x}}
4219:Calinski-Harabasz index
3371:10.1109/msp.2008.930649
3323:10.1364/JOSAA.24.000B61
2862:10.1109/TIP.2003.819861
2677:{\displaystyle y=h*x+n}
1726:Mathematical Properties
85:Universal Quality Index
3944:. pp. 2366–2369.
3661:. pp. 1477–1480.
3548:. pp. 2929–2932.
3204:(1): 011003–011003–9.
2774:Performance comparison
2758:
2738:
2718:
2698:
2678:
2463:
2443:
2423:
2396:
2376:
2347:
2279:
2205:
2117:
2060:
1979:
1877:
1716:
1682:
1556:
1503:
1397:
1268:
1138:
1118:
1098:
1078:
1058:
1029:
996:
961:
882:
860:
804:
746:
726:
702:
670:
646:
612:
588:
554:
530:
501:
477:
445:
212:
186:
166:
118:University of Waterloo
4382:Intra-list Similarity
3950:10.1109/icpr.2010.579
2780:video quality metrics
2759:
2739:
2719:
2699:
2679:
2464:
2444:
2424:
2422:{\displaystyle c_{y}}
2397:
2377:
2375:{\displaystyle c_{x}}
2348:
2259:
2185:
2097:
2040:
1959:
1878:
1717:
1683:
1557:
1504:
1398:
1269:
1139:
1119:
1099:
1079:
1059:
1030:
997:
962:
883:
861:
805:
747:
727:
703:
671:
647:
613:
589:
555:
531:
502:
478:
446:
213:
187:
167:
50:full reference metric
39:structural similarity
32:SSIM (disambiguation)
3995:C/C++ Implementation
3763:. pp. 765–768.
2748:
2728:
2724:is the blur kernel,
2708:
2688:
2650:
2453:
2433:
2406:
2386:
2359:
1906:
1895:Complex Wavelet SSIM
1808:
1782:Three-component SSIM
1776:Multi-component SSIM
1694:
1690:Setting the weights
1571:
1518:
1408:
1279:
1150:
1128:
1108:
1088:
1068:
1048:
1006:
973:
896:
872:
814:
758:
736:
716:
682:
660:
624:
602:
566:
544:
513:
491:
460:
224:
196:
176:
156:
3990:Rust Implementation
3722:2011ITIP...20.1185W
3421:2015SPIE.9394E..06R
3363:2009ISPM...26...98W
3305:2007JOSAA..24...61W
3210:2010JEI....19a1003L
3022:2012ITIP...21.1488B
2844:2004ITIP...13..600W
2642:Image Restoration:
2321:
2242:
1791:four-component SSIM
1376:
1358:
1247:
1229:
641:
583:
421:
403:
369:
351:
114:New York University
4403:Euclidean distance
4369:Recommender system
4249:Similarity measure
4063:evaluation metrics
3429:10.1117/12.2077917
3271:www.compression.ru
3117:Electronic Imaging
2904:scholar.google.com
2796:Mean squared error
2754:
2734:
2714:
2694:
2674:
2459:
2439:
2419:
2392:
2372:
2343:
2301:
2222:
1873:
1850:
1816:
1712:
1678:
1552:
1499:
1393:
1362:
1344:
1264:
1233:
1215:
1134:
1114:
1094:
1074:
1054:
1040:Formula components
1025:
992:
957:
878:
856:
800:
742:
722:
698:
666:
642:
627:
608:
584:
569:
550:
526:
497:
473:
441:
407:
389:
355:
337:
232:
208:
182:
162:
142:Television Academy
4429:
4428:
4398:Cosine similarity
4234:Hopkins statistic
3959:978-1-4244-7542-1
3918:978-1-4244-1436-9
3846:Journal of Vision
3788:978-1-4244-1483-3
3686:978-1-4673-2533-2
3523:10.1118/1.3605634
3218:10.1117/1.3267087
2976:978-0-7803-8104-9
2757:{\displaystyle x}
2737:{\displaystyle n}
2717:{\displaystyle h}
2697:{\displaystyle y}
2644:Image restoration
2637:image compression
2462:{\displaystyle K}
2442:{\displaystyle y}
2395:{\displaystyle x}
2334:
2158:
1912:
1871:
1849:
1815:
1732:distance function
1577:
1497:
1391:
1262:
1137:{\displaystyle s}
1124:) and structure (
1117:{\displaystyle c}
1097:{\displaystyle l}
1077:{\displaystyle y}
1057:{\displaystyle x}
933:
921:
881:{\displaystyle L}
745:{\displaystyle y}
725:{\displaystyle x}
669:{\displaystyle y}
611:{\displaystyle x}
553:{\displaystyle y}
538:pixel sample mean
500:{\displaystyle x}
485:pixel sample mean
439:
231:
185:{\displaystyle y}
165:{\displaystyle x}
16:(Redirected from
4449:
4442:Image processing
4421:Confusion matrix
4196:Logarithmic Loss
4061:Machine learning
4054:
4047:
4040:
4031:
3972:
3971:
3937:
3931:
3930:
3902:
3886:
3880:
3879:
3869:
3843:
3834:
3828:
3827:
3807:
3801:
3800:
3772:
3756:
3750:
3749:
3716:(5): 1185–1198.
3705:
3699:
3698:
3670:
3654:
3648:
3647:
3645:
3634:
3625:
3624:
3614:
3582:
3576:
3575:
3541:
3535:
3534:
3517:(8): 4512–4517.
3505:
3499:
3498:
3487:
3481:
3480:
3473:
3467:
3466:
3456:
3447:
3441:
3440:
3406:
3397:
3391:
3390:
3346:
3335:
3334:
3316:
3290:
3281:
3275:
3274:
3263:
3257:
3256:
3236:
3230:
3229:
3193:
3187:
3186:
3150:
3141:
3140:
3114:
3105:
3094:
3093:
3083:
3059:
3050:
3049:
3016:(4): 2324–2328.
3007:
2998:
2989:
2988:
2960:
2944:
2931:
2930:
2928:
2920:
2914:
2913:
2911:
2910:
2900:"Google Scholar"
2896:
2890:
2889:
2855:
2827:
2763:
2761:
2760:
2755:
2743:
2741:
2740:
2735:
2723:
2721:
2720:
2715:
2703:
2701:
2700:
2695:
2683:
2681:
2680:
2675:
2611:
2607:
2603:
2583:
2582:
2580:
2579:
2561:
2558:
2468:
2466:
2465:
2460:
2449:. Additionally,
2448:
2446:
2445:
2440:
2428:
2426:
2425:
2420:
2418:
2417:
2401:
2399:
2398:
2393:
2381:
2379:
2378:
2373:
2371:
2370:
2352:
2350:
2349:
2344:
2342:
2341:
2335:
2333:
2326:
2320:
2315:
2300:
2299:
2284:
2278:
2273:
2254:
2247:
2241:
2236:
2221:
2220:
2204:
2199:
2184:
2175:
2173:
2172:
2166:
2165:
2159:
2157:
2150:
2149:
2144:
2138:
2137:
2122:
2116:
2111:
2093:
2092:
2087:
2081:
2080:
2065:
2059:
2054:
2038:
2031:
2026:
2025:
2010:
2005:
2000:
1999:
1984:
1978:
1973:
1954:
1952:
1951:
1939:
1938:
1926:
1925:
1913:
1910:
1882:
1880:
1879:
1874:
1872:
1867:
1851:
1847:
1837:
1817:
1813:
1793:
1792:
1784:
1783:
1767:Multi-Scale SSIM
1721:
1719:
1718:
1713:
1687:
1685:
1684:
1679:
1677:
1676:
1649:
1648:
1621:
1620:
1578:
1575:
1561:
1559:
1558:
1553:
1548:
1543:
1542:
1530:
1529:
1508:
1506:
1505:
1500:
1498:
1496:
1495:
1494:
1482:
1481:
1472:
1471:
1461:
1460:
1459:
1447:
1446:
1433:
1402:
1400:
1399:
1394:
1392:
1390:
1389:
1388:
1375:
1370:
1357:
1352:
1342:
1341:
1340:
1328:
1327:
1318:
1317:
1304:
1273:
1271:
1270:
1265:
1263:
1261:
1260:
1259:
1246:
1241:
1228:
1223:
1213:
1212:
1211:
1199:
1198:
1189:
1188:
1175:
1143:
1141:
1140:
1135:
1123:
1121:
1120:
1115:
1103:
1101:
1100:
1095:
1083:
1081:
1080:
1075:
1063:
1061:
1060:
1055:
1034:
1032:
1031:
1026:
1018:
1017:
1001:
999:
998:
993:
985:
984:
966:
964:
963:
958:
950:
949:
931:
919:
887:
885:
884:
879:
865:
863:
862:
857:
855:
854:
842:
841:
826:
825:
809:
807:
806:
801:
799:
798:
786:
785:
770:
769:
751:
749:
748:
743:
731:
729:
728:
723:
707:
705:
704:
699:
697:
696:
675:
673:
672:
667:
651:
649:
648:
643:
640:
635:
617:
615:
614:
609:
593:
591:
590:
585:
582:
577:
559:
557:
556:
551:
535:
533:
532:
527:
525:
524:
506:
504:
503:
498:
482:
480:
479:
474:
472:
471:
450:
448:
447:
442:
440:
438:
434:
433:
420:
415:
402:
397:
382:
381:
368:
363:
350:
345:
332:
328:
327:
315:
314:
293:
292:
280:
279:
270:
269:
253:
233:
229:
217:
215:
214:
209:
191:
189:
188:
183:
171:
169:
168:
163:
89:Wang–Bovik Index
21:
4457:
4456:
4452:
4451:
4450:
4448:
4447:
4446:
4432:
4431:
4430:
4425:
4412:
4386:
4363:
4354:Inception score
4342:
4319:
4297:Computer Vision
4291:
4263:
4200:
4132:
4064:
4058:
3981:
3976:
3975:
3960:
3939:
3938:
3934:
3919:
3900:10.1.1.159.5710
3888:
3887:
3883:
3841:
3836:
3835:
3831:
3809:
3808:
3804:
3789:
3770:10.1.1.152.7952
3758:
3757:
3753:
3707:
3706:
3702:
3687:
3668:10.1.1.476.2566
3656:
3655:
3651:
3643:
3636:
3635:
3628:
3584:
3583:
3579:
3564:
3543:
3542:
3538:
3511:Medical Physics
3507:
3506:
3502:
3497:. 14 June 2017.
3495:Cloudinary Blog
3489:
3488:
3484:
3475:
3474:
3470:
3454:
3449:
3448:
3444:
3404:
3399:
3398:
3394:
3348:
3347:
3338:
3314:10.1.1.113.4177
3299:(12): B61–B69.
3288:
3283:
3282:
3278:
3267:"Redirect page"
3265:
3264:
3260:
3238:
3237:
3233:
3195:
3194:
3190:
3152:
3151:
3144:
3112:
3107:
3106:
3097:
3061:
3060:
3053:
3005:
3000:
2999:
2992:
2977:
2946:
2945:
2934:
2926:
2922:
2921:
2917:
2908:
2906:
2898:
2897:
2893:
2829:
2828:
2824:
2819:
2792:
2776:
2746:
2745:
2726:
2725:
2706:
2705:
2686:
2685:
2648:
2647:
2629:
2609:
2605:
2601:
2593:
2585:
2578:
2570:
2562:
2559:
2557:
2549:
2548:
2546:
2533:
2530:
2509:
2489:
2476:
2451:
2450:
2431:
2430:
2409:
2404:
2403:
2384:
2383:
2362:
2357:
2356:
2285:
2255:
2206:
2176:
2139:
2123:
2082:
2066:
2039:
2011:
1985:
1955:
1930:
1917:
1904:
1903:
1897:
1888:
1838:
1806:
1805:
1800:
1790:
1789:
1781:
1780:
1778:
1769:
1764:
1744:
1728:
1692:
1691:
1668:
1640:
1612:
1569:
1568:
1534:
1521:
1516:
1515:
1486:
1473:
1463:
1462:
1451:
1435:
1434:
1406:
1405:
1380:
1343:
1332:
1319:
1309:
1305:
1277:
1276:
1251:
1214:
1203:
1190:
1180:
1176:
1148:
1147:
1126:
1125:
1106:
1105:
1086:
1085:
1066:
1065:
1046:
1045:
1042:
1009:
1004:
1003:
976:
971:
970:
899:
894:
893:
870:
869:
846:
833:
817:
812:
811:
790:
777:
761:
756:
755:
734:
733:
714:
713:
685:
680:
679:
658:
657:
622:
621:
600:
599:
564:
563:
542:
541:
516:
511:
510:
489:
488:
463:
458:
457:
425:
373:
333:
319:
303:
284:
271:
261:
254:
222:
221:
194:
193:
192:of common size
174:
173:
154:
153:
150:
140:in 2015 by the
97:Eero Simoncelli
81:
73:absolute errors
35:
28:
23:
22:
15:
12:
11:
5:
4455:
4453:
4445:
4444:
4434:
4433:
4427:
4426:
4424:
4423:
4417:
4414:
4413:
4411:
4410:
4405:
4400:
4394:
4392:
4388:
4387:
4385:
4384:
4379:
4373:
4371:
4365:
4364:
4362:
4361:
4356:
4350:
4348:
4344:
4343:
4341:
4340:
4335:
4329:
4327:
4321:
4320:
4318:
4317:
4312:
4307:
4301:
4299:
4293:
4292:
4290:
4289:
4284:
4279:
4273:
4271:
4265:
4264:
4262:
4261:
4256:
4251:
4246:
4241:
4236:
4231:
4226:
4224:Davies-Bouldin
4221:
4216:
4210:
4208:
4202:
4201:
4199:
4198:
4193:
4188:
4183:
4178:
4173:
4168:
4163:
4158:
4153:
4148:
4142:
4140:
4138:Classification
4134:
4133:
4131:
4130:
4125:
4120:
4115:
4110:
4105:
4100:
4095:
4090:
4085:
4080:
4074:
4072:
4066:
4065:
4059:
4057:
4056:
4049:
4042:
4034:
4028:
4027:
4022:
4017:
4012:
4007:
4002:
3997:
3992:
3987:
3980:
3979:External links
3977:
3974:
3973:
3958:
3932:
3917:
3881:
3858:10.1167/8.12.8
3852:(12): 8.1–13.
3829:
3818:(2): 604–608.
3802:
3787:
3751:
3700:
3685:
3649:
3626:
3577:
3562:
3536:
3500:
3482:
3468:
3442:
3392:
3336:
3276:
3258:
3247:(7): 517–526.
3231:
3188:
3142:
3095:
3074:(2): 121–132.
3051:
2990:
2975:
2958:10.1.1.58.1939
2932:
2915:
2891:
2838:(4): 600–612.
2821:
2820:
2818:
2815:
2814:
2813:
2808:
2803:
2798:
2791:
2788:
2775:
2772:
2771:
2770:
2766:
2753:
2733:
2713:
2693:
2673:
2670:
2667:
2664:
2661:
2658:
2655:
2640:
2628:
2625:
2597:
2589:
2574:
2566:
2553:
2529:
2526:
2508:
2505:
2488:
2485:
2475:
2472:
2458:
2438:
2416:
2412:
2391:
2369:
2365:
2340:
2332:
2329:
2325:
2319:
2314:
2311:
2308:
2304:
2298:
2295:
2292:
2288:
2283:
2277:
2272:
2269:
2266:
2262:
2258:
2253:
2250:
2246:
2240:
2235:
2232:
2229:
2225:
2219:
2216:
2213:
2209:
2203:
2198:
2195:
2192:
2188:
2183:
2179:
2171:
2164:
2156:
2153:
2148:
2143:
2136:
2133:
2130:
2126:
2121:
2115:
2110:
2107:
2104:
2100:
2096:
2091:
2086:
2079:
2076:
2073:
2069:
2064:
2058:
2053:
2050:
2047:
2043:
2037:
2034:
2030:
2024:
2021:
2018:
2014:
2009:
2004:
1998:
1995:
1992:
1988:
1983:
1977:
1972:
1969:
1966:
1962:
1958:
1950:
1945:
1942:
1937:
1933:
1929:
1924:
1920:
1916:
1896:
1893:
1887:
1884:
1870:
1866:
1863:
1860:
1857:
1854:
1844:
1841:
1835:
1832:
1829:
1826:
1823:
1820:
1799:
1796:
1777:
1774:
1768:
1765:
1763:
1760:
1743:
1740:
1727:
1724:
1711:
1708:
1705:
1702:
1699:
1675:
1671:
1667:
1664:
1661:
1658:
1655:
1652:
1647:
1643:
1639:
1636:
1633:
1630:
1627:
1624:
1619:
1615:
1611:
1608:
1605:
1602:
1599:
1596:
1593:
1590:
1587:
1584:
1581:
1563:
1562:
1551:
1547:
1541:
1537:
1533:
1528:
1524:
1493:
1489:
1485:
1480:
1476:
1470:
1466:
1458:
1454:
1450:
1445:
1442:
1438:
1431:
1428:
1425:
1422:
1419:
1416:
1413:
1387:
1383:
1379:
1374:
1369:
1365:
1361:
1356:
1351:
1347:
1339:
1335:
1331:
1326:
1322:
1316:
1312:
1308:
1302:
1299:
1296:
1293:
1290:
1287:
1284:
1258:
1254:
1250:
1245:
1240:
1236:
1232:
1227:
1222:
1218:
1210:
1206:
1202:
1197:
1193:
1187:
1183:
1179:
1173:
1170:
1167:
1164:
1161:
1158:
1155:
1133:
1113:
1093:
1073:
1053:
1041:
1038:
1037:
1036:
1024:
1021:
1016:
1012:
991:
988:
983:
979:
968:
956:
953:
948:
945:
942:
939:
936:
930:
927:
924:
918:
915:
912:
909:
906:
902:
877:
867:
853:
849:
845:
840:
836:
832:
829:
824:
820:
797:
793:
789:
784:
780:
776:
773:
768:
764:
753:
741:
721:
695:
692:
688:
677:
665:
639:
634:
630:
619:
607:
581:
576:
572:
561:
549:
523:
519:
508:
496:
470:
466:
437:
432:
428:
424:
419:
414:
410:
406:
401:
396:
392:
388:
385:
380:
376:
372:
367:
362:
358:
354:
349:
344:
340:
336:
331:
326:
322:
318:
313:
310:
306:
302:
299:
296:
291:
287:
283:
278:
274:
268:
264:
260:
257:
251:
248:
245:
242:
239:
236:
207:
204:
201:
181:
161:
149:
146:
125:Google Scholar
80:
77:
26:
24:
14:
13:
10:
9:
6:
4:
3:
2:
4454:
4443:
4440:
4439:
4437:
4422:
4419:
4418:
4415:
4409:
4406:
4404:
4401:
4399:
4396:
4395:
4393:
4389:
4383:
4380:
4378:
4375:
4374:
4372:
4370:
4366:
4360:
4357:
4355:
4352:
4351:
4349:
4345:
4339:
4336:
4334:
4331:
4330:
4328:
4326:
4322:
4316:
4313:
4311:
4308:
4306:
4303:
4302:
4300:
4298:
4294:
4288:
4285:
4283:
4280:
4278:
4275:
4274:
4272:
4270:
4266:
4260:
4257:
4255:
4252:
4250:
4247:
4245:
4242:
4240:
4239:Jaccard index
4237:
4235:
4232:
4230:
4227:
4225:
4222:
4220:
4217:
4215:
4212:
4211:
4209:
4207:
4203:
4197:
4194:
4192:
4189:
4187:
4184:
4182:
4179:
4177:
4174:
4172:
4169:
4167:
4164:
4162:
4159:
4157:
4154:
4152:
4149:
4147:
4144:
4143:
4141:
4139:
4135:
4129:
4126:
4124:
4121:
4119:
4116:
4114:
4111:
4109:
4106:
4104:
4101:
4099:
4096:
4094:
4091:
4089:
4086:
4084:
4081:
4079:
4076:
4075:
4073:
4071:
4067:
4062:
4055:
4050:
4048:
4043:
4041:
4036:
4035:
4032:
4026:
4023:
4021:
4018:
4016:
4013:
4011:
4008:
4006:
4003:
4001:
3998:
3996:
3993:
3991:
3988:
3986:
3983:
3982:
3978:
3969:
3965:
3961:
3955:
3951:
3947:
3943:
3936:
3933:
3928:
3924:
3920:
3914:
3910:
3906:
3901:
3896:
3892:
3885:
3882:
3877:
3873:
3868:
3863:
3859:
3855:
3851:
3847:
3840:
3833:
3830:
3825:
3821:
3817:
3813:
3806:
3803:
3798:
3794:
3790:
3784:
3780:
3776:
3771:
3766:
3762:
3755:
3752:
3747:
3743:
3739:
3735:
3731:
3727:
3723:
3719:
3715:
3711:
3704:
3701:
3696:
3692:
3688:
3682:
3678:
3674:
3669:
3664:
3660:
3653:
3650:
3642:
3641:
3633:
3631:
3627:
3622:
3618:
3613:
3608:
3604:
3600:
3597:(3): 035501.
3596:
3592:
3588:
3581:
3578:
3573:
3569:
3565:
3563:1-4244-0480-0
3559:
3555:
3551:
3547:
3540:
3537:
3532:
3528:
3524:
3520:
3516:
3512:
3504:
3501:
3496:
3492:
3486:
3483:
3478:
3472:
3469:
3464:
3460:
3453:
3446:
3443:
3438:
3434:
3430:
3426:
3422:
3418:
3414:
3410:
3403:
3396:
3393:
3388:
3384:
3380:
3376:
3372:
3368:
3364:
3360:
3357:(1): 98–117.
3356:
3352:
3345:
3343:
3341:
3337:
3332:
3328:
3324:
3320:
3315:
3310:
3306:
3302:
3298:
3294:
3287:
3280:
3277:
3272:
3268:
3262:
3259:
3254:
3250:
3246:
3242:
3235:
3232:
3227:
3223:
3219:
3215:
3211:
3207:
3203:
3199:
3192:
3189:
3184:
3180:
3176:
3172:
3168:
3164:
3160:
3156:
3149:
3147:
3143:
3138:
3134:
3130:
3126:
3122:
3118:
3111:
3104:
3102:
3100:
3096:
3091:
3087:
3082:
3081:10.1.1.2.6330
3077:
3073:
3069:
3065:
3058:
3056:
3052:
3047:
3043:
3039:
3035:
3031:
3027:
3023:
3019:
3015:
3011:
3004:
2997:
2995:
2991:
2986:
2982:
2978:
2972:
2968:
2964:
2959:
2954:
2950:
2943:
2941:
2939:
2937:
2933:
2925:
2919:
2916:
2905:
2901:
2895:
2892:
2887:
2883:
2879:
2875:
2871:
2867:
2863:
2859:
2854:
2853:10.1.1.2.5689
2849:
2845:
2841:
2837:
2833:
2826:
2823:
2816:
2812:
2811:Video quality
2809:
2807:
2804:
2802:
2799:
2797:
2794:
2793:
2789:
2787:
2783:
2781:
2773:
2767:
2751:
2731:
2711:
2691:
2671:
2668:
2665:
2662:
2659:
2656:
2653:
2645:
2641:
2638:
2634:
2633:
2632:
2626:
2624:
2620:
2618:
2613:
2600:
2596:
2592:
2588:
2577:
2573:
2569:
2565:
2556:
2552:
2544:
2540:
2536:
2527:
2525:
2523:
2518:
2514:
2506:
2504:
2502:
2498:
2494:
2486:
2484:
2480:
2473:
2471:
2456:
2436:
2414:
2410:
2389:
2367:
2363:
2353:
2330:
2327:
2317:
2312:
2309:
2306:
2302:
2296:
2293:
2290:
2286:
2275:
2270:
2267:
2264:
2260:
2256:
2251:
2248:
2238:
2233:
2230:
2227:
2223:
2217:
2214:
2211:
2207:
2201:
2196:
2193:
2190:
2186:
2177:
2154:
2151:
2146:
2134:
2131:
2128:
2124:
2113:
2108:
2105:
2102:
2098:
2094:
2089:
2077:
2074:
2071:
2067:
2056:
2051:
2048:
2045:
2041:
2035:
2032:
2022:
2019:
2016:
2012:
1996:
1993:
1990:
1986:
1975:
1970:
1967:
1964:
1960:
1956:
1943:
1935:
1931:
1927:
1922:
1918:
1901:
1894:
1892:
1885:
1883:
1868:
1861:
1858:
1855:
1842:
1839:
1833:
1827:
1824:
1821:
1803:
1797:
1795:
1786:
1775:
1773:
1766:
1761:
1759:
1757:
1753:
1749:
1741:
1739:
1737:
1733:
1725:
1723:
1709:
1706:
1703:
1700:
1697:
1688:
1673:
1665:
1662:
1659:
1653:
1650:
1645:
1637:
1634:
1631:
1625:
1622:
1617:
1609:
1606:
1603:
1597:
1594:
1588:
1585:
1582:
1566:
1549:
1545:
1539:
1535:
1531:
1526:
1522:
1514:
1513:
1512:
1509:
1491:
1487:
1483:
1478:
1474:
1468:
1464:
1456:
1452:
1448:
1443:
1440:
1436:
1429:
1423:
1420:
1417:
1411:
1403:
1385:
1381:
1377:
1372:
1367:
1363:
1359:
1354:
1349:
1345:
1337:
1333:
1329:
1324:
1320:
1314:
1310:
1306:
1300:
1294:
1291:
1288:
1282:
1274:
1256:
1252:
1248:
1243:
1238:
1234:
1230:
1225:
1220:
1216:
1208:
1204:
1200:
1195:
1191:
1185:
1181:
1177:
1171:
1165:
1162:
1159:
1153:
1145:
1131:
1111:
1104:), contrast (
1091:
1084:: luminance (
1071:
1051:
1039:
1022:
1019:
1014:
1010:
989:
986:
981:
977:
969:
954:
951:
946:
943:
940:
937:
934:
928:
925:
922:
916:
913:
910:
907:
900:
891:
890:dynamic range
875:
868:
851:
843:
838:
834:
827:
822:
818:
795:
787:
782:
778:
771:
766:
762:
754:
739:
719:
711:
693:
690:
686:
678:
663:
655:
637:
632:
628:
620:
605:
597:
579:
574:
570:
562:
547:
539:
521:
517:
509:
494:
486:
468:
464:
456:
455:
454:
451:
430:
426:
422:
417:
412:
408:
404:
399:
394:
390:
378:
374:
370:
365:
360:
356:
352:
347:
342:
338:
324:
320:
316:
311:
308:
304:
300:
289:
285:
281:
276:
272:
266:
262:
258:
249:
243:
240:
237:
219:
205:
202:
199:
179:
159:
147:
145:
143:
139:
134:
130:
126:
121:
119:
115:
111:
106:
104:
103:
98:
94:
90:
86:
78:
76:
74:
70:
66:
62:
57:
55:
54:image quality
51:
47:
43:
42:index measure
40:
33:
19:
3941:
3935:
3890:
3884:
3849:
3845:
3832:
3815:
3811:
3805:
3760:
3754:
3713:
3709:
3703:
3658:
3652:
3639:
3594:
3590:
3580:
3545:
3539:
3514:
3510:
3503:
3494:
3485:
3471:
3462:
3458:
3445:
3412:
3408:
3395:
3354:
3350:
3296:
3292:
3279:
3270:
3261:
3244:
3240:
3234:
3201:
3197:
3191:
3161:(1): 81–91.
3158:
3154:
3120:
3116:
3071:
3067:
3013:
3009:
2948:
2918:
2907:. Retrieved
2903:
2894:
2835:
2831:
2825:
2784:
2777:
2630:
2621:
2614:
2598:
2594:
2590:
2586:
2575:
2571:
2567:
2563:
2554:
2550:
2542:
2538:
2534:
2531:
2510:
2496:
2492:
2490:
2481:
2477:
2354:
1902:
1898:
1889:
1804:
1801:
1787:
1779:
1770:
1745:
1729:
1689:
1567:
1564:
1510:
1404:
1275:
1146:
1043:
452:
220:
151:
122:
107:
100:
88:
84:
82:
72:
60:
58:
45:
41:
38:
36:
3123:(13): 1–7.
2627:Application
1736:quasiconvex
1035:by default.
4391:Similarity
4333:Perplexity
4244:Rand index
4229:Dunn index
4214:Silhouette
4206:Clustering
4070:Regression
3415:: 939406.
2909:2019-07-04
2817:References
2513:Cloudinary
2507:SSIMULACRA
2497:continuous
710:covariance
93:Alan Bovik
87:(UQI), or
4161:Precision
4113:RMSE/RMSD
3985:Home page
3895:CiteSeerX
3765:CiteSeerX
3663:CiteSeerX
3379:1053-5888
3309:CiteSeerX
3226:1017-9909
3175:1863-1703
3076:CiteSeerX
2953:CiteSeerX
2886:207761262
2870:1057-7149
2848:CiteSeerX
2663:∗
2318:∗
2261:∑
2239:∗
2187:∑
2099:∑
2042:∑
1961:∑
1843:−
1710:γ
1704:β
1698:α
1674:γ
1651:⋅
1646:β
1623:⋅
1618:α
1475:σ
1465:σ
1437:σ
1364:σ
1346:σ
1321:σ
1311:σ
1235:μ
1217:μ
1192:μ
1182:μ
952:−
905:#
687:σ
629:σ
571:σ
518:μ
465:μ
409:σ
391:σ
357:μ
339:μ
305:σ
273:μ
263:μ
203:×
148:Algorithm
4436:Category
4377:Coverage
4156:Accuracy
3876:18831621
3797:14830268
3738:21078577
3695:10716320
3621:28924574
3572:15809337
3531:21928621
3465:: 27–32.
3331:18059915
3183:30046880
3137:26253431
3046:13739220
3038:22042163
2985:60600316
2878:15376593
2790:See also
2765:authors.
2617:gradient
2493:discrete
2474:SSIMPLUS
1762:Variants
654:variance
596:variance
4269:Ranking
4259:SimHash
4146:F-score
3968:9506273
3927:1685021
3867:4143340
3718:Bibcode
3612:5527267
3437:1466973
3417:Bibcode
3387:2492436
3359:Bibcode
3301:Bibcode
3206:Bibcode
3018:Bibcode
2840:Bibcode
2581:
2547:
2522:JPEG XL
1911:CW-SSIM
79:History
4166:Recall
3966:
3956:
3925:
3915:
3897:
3874:
3864:
3795:
3785:
3767:
3746:106021
3744:
3736:
3693:
3683:
3665:
3619:
3609:
3570:
3560:
3529:
3435:
3385:
3377:
3329:
3311:
3224:
3181:
3173:
3135:
3078:
3044:
3036:
2983:
2973:
2955:
2884:
2876:
2868:
2850:
2684:where
2595:σ
2587:σ
2572:σ
2564:σ
2551:σ
2355:Where
932:
920:
453:with:
4171:Kappa
4088:sMAPE
3964:S2CID
3923:S2CID
3842:(PDF)
3793:S2CID
3742:S2CID
3691:S2CID
3644:(PDF)
3568:S2CID
3455:(PDF)
3433:S2CID
3405:(PDF)
3383:S2CID
3289:(PDF)
3179:S2CID
3133:S2CID
3113:(PDF)
3042:S2CID
3006:(PDF)
2981:S2CID
2927:(PDF)
2882:S2CID
2584:when
2487:cSSIM
1814:DSSIM
1756:YCbCr
4338:BLEU
4310:SSIM
4305:PSNR
4282:NDCG
4103:MSPE
4098:MASE
4093:MAPE
3954:ISBN
3913:ISBN
3872:PMID
3783:ISBN
3734:PMID
3681:ISBN
3617:PMID
3558:ISBN
3527:PMID
3413:9394
3375:ISSN
3327:PMID
3222:ISSN
3171:ISSN
3121:2016
3034:PMID
2971:ISBN
2874:PMID
2866:ISSN
2545:) =
2402:and
1848:SSIM
1748:luma
1576:SSIM
1064:and
1023:0.03
1002:and
990:0.01
888:the
732:and
708:the
652:the
594:the
536:the
483:the
230:SSIM
218:is:
172:and
69:PSNR
46:SSIM
37:The
18:SSIM
4359:FID
4325:NLP
4315:IoU
4277:MRR
4254:SMC
4186:ROC
4181:AUC
4176:MCC
4128:MAD
4123:MDA
4108:RMS
4083:MAE
4078:MSE
3946:doi
3905:doi
3862:PMC
3854:doi
3820:doi
3775:doi
3726:doi
3673:doi
3607:PMC
3599:doi
3550:doi
3519:doi
3425:doi
3367:doi
3319:doi
3249:doi
3214:doi
3163:doi
3125:doi
3086:doi
3026:doi
2963:doi
2858:doi
2602:≠0
2517:XYB
1752:RGB
712:of
656:of
598:of
540:of
487:of
67:or
65:MSE
4438::
4287:AP
4151:P4
3962:.
3952:.
3921:.
3911:.
3903:.
3870:.
3860:.
3848:.
3844:.
3816:69
3814:.
3791:.
3781:.
3773:.
3740:.
3732:.
3724:.
3714:20
3712:.
3689:.
3679:.
3671:.
3629:^
3615:.
3605:.
3593:.
3589:.
3566:.
3556:.
3525:.
3515:38
3513:.
3493:.
3463:14
3461:.
3457:.
3431:.
3423:.
3407:.
3381:.
3373:.
3365:.
3355:26
3353:.
3339:^
3325:.
3317:.
3307:.
3297:24
3295:.
3291:.
3269:.
3245:25
3243:.
3220:.
3212:.
3202:19
3200:.
3177:.
3169:.
3157:.
3145:^
3131:.
3119:.
3115:.
3098:^
3084:.
3072:19
3070:.
3066:.
3054:^
3040:.
3032:.
3024:.
3014:21
3012:.
3008:.
2993:^
2979:.
2969:.
2961:.
2935:^
2902:.
2880:.
2872:.
2864:.
2856:.
2846:.
2836:13
2834:.
2604:,
2555:xy
2541:,
2537:*(
2524:.
2503:.
967:);
810:,
144:.
4118:R
4053:e
4046:t
4039:v
3970:.
3948::
3929:.
3907::
3878:.
3856::
3850:8
3826:.
3822::
3799:.
3777::
3748:.
3728::
3720::
3697:.
3675::
3623:.
3601::
3595:4
3574:.
3552::
3533:.
3521::
3439:.
3427::
3419::
3389:.
3369::
3361::
3333:.
3321::
3303::
3273:.
3255:.
3251::
3228:.
3216::
3208::
3185:.
3165::
3159:5
3139:.
3127::
3092:.
3088::
3048:.
3028::
3020::
2987:.
2965::
2929:.
2912:.
2888:.
2860::
2842::
2752:x
2732:n
2712:h
2692:y
2672:n
2669:+
2666:x
2660:h
2657:=
2654:y
2610:0
2606:1
2599:y
2591:x
2576:y
2568:x
2560:/
2543:y
2539:x
2535:r
2457:K
2437:y
2415:y
2411:c
2390:x
2368:x
2364:c
2339:)
2331:K
2328:+
2324:|
2313:i
2310:,
2307:y
2303:c
2297:i
2294:,
2291:x
2287:c
2282:|
2276:N
2271:1
2268:=
2265:i
2257:2
2252:K
2249:+
2245:|
2234:i
2231:,
2228:y
2224:c
2218:i
2215:,
2212:x
2208:c
2202:N
2197:1
2194:=
2191:i
2182:|
2178:2
2170:(
2163:)
2155:K
2152:+
2147:2
2142:|
2135:i
2132:,
2129:y
2125:c
2120:|
2114:N
2109:1
2106:=
2103:i
2095:+
2090:2
2085:|
2078:i
2075:,
2072:x
2068:c
2063:|
2057:N
2052:1
2049:=
2046:i
2036:K
2033:+
2029:|
2023:i
2020:,
2017:y
2013:c
2008:|
2003:|
1997:i
1994:,
1991:x
1987:c
1982:|
1976:N
1971:1
1968:=
1965:i
1957:2
1949:(
1944:=
1941:)
1936:y
1932:c
1928:,
1923:x
1919:c
1915:(
1869:2
1865:)
1862:y
1859:,
1856:x
1853:(
1840:1
1834:=
1831:)
1828:y
1825:,
1822:x
1819:(
1707:,
1701:,
1670:)
1666:y
1663:,
1660:x
1657:(
1654:s
1642:)
1638:y
1635:,
1632:x
1629:(
1626:c
1614:)
1610:y
1607:,
1604:x
1601:(
1598:l
1595:=
1592:)
1589:y
1586:,
1583:x
1580:(
1550:2
1546:/
1540:2
1536:c
1532:=
1527:3
1523:c
1492:3
1488:c
1484:+
1479:y
1469:x
1457:3
1453:c
1449:+
1444:y
1441:x
1430:=
1427:)
1424:y
1421:,
1418:x
1415:(
1412:s
1386:2
1382:c
1378:+
1373:2
1368:y
1360:+
1355:2
1350:x
1338:2
1334:c
1330:+
1325:y
1315:x
1307:2
1301:=
1298:)
1295:y
1292:,
1289:x
1286:(
1283:c
1257:1
1253:c
1249:+
1244:2
1239:y
1231:+
1226:2
1221:x
1209:1
1205:c
1201:+
1196:y
1186:x
1178:2
1172:=
1169:)
1166:y
1163:,
1160:x
1157:(
1154:l
1132:s
1112:c
1092:l
1072:y
1052:x
1020:=
1015:2
1011:k
987:=
982:1
978:k
955:1
947:l
944:e
941:x
938:i
935:p
929:r
926:e
923:p
917:s
914:t
911:i
908:b
901:2
876:L
852:2
848:)
844:L
839:2
835:k
831:(
828:=
823:2
819:c
796:2
792:)
788:L
783:1
779:k
775:(
772:=
767:1
763:c
752:;
740:y
720:x
694:y
691:x
676:;
664:y
638:2
633:y
618:;
606:x
580:2
575:x
560:;
548:y
522:y
507:;
495:x
469:x
436:)
431:2
427:c
423:+
418:2
413:y
405:+
400:2
395:x
387:(
384:)
379:1
375:c
371:+
366:2
361:y
353:+
348:2
343:x
335:(
330:)
325:2
321:c
317:+
312:y
309:x
301:2
298:(
295:)
290:1
286:c
282:+
277:y
267:x
259:2
256:(
250:=
247:)
244:y
241:,
238:x
235:(
206:N
200:N
180:y
160:x
44:(
34:.
20:)
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.