reference_images

所属分类:图形图像处理
开发工具:Visual C++
文件大小:9097KB
下载次数:25
上传日期:2014-02-11 07:32:22
上 传 者leiyu
说明:  TID2013的部部分图片数据,用于图像质量评级
(TID2013 a portion of the picture data for image quality rating)

文件列表:
reference_images (0, 2014-02-11)
reference_images\I01.BMP (589878, 2007-01-15)
reference_images\I02.BMP (589878, 2007-01-15)
reference_images\I03.BMP (589878, 2007-01-15)
reference_images\I04.BMP (589878, 2007-01-15)
reference_images\I05.BMP (589878, 2007-01-15)
reference_images\I06.BMP (589878, 2007-01-15)
reference_images\I07.BMP (589878, 2007-01-15)
reference_images\I08.BMP (589878, 2007-01-15)
reference_images\I09.BMP (589878, 2007-01-15)
reference_images\I10.BMP (589878, 2007-01-15)
reference_images\I11.BMP (589878, 2007-01-15)
reference_images\I12.BMP (589878, 2007-01-15)
reference_images\I13.BMP (589878, 2007-01-15)
reference_images\I14.BMP (589878, 2007-01-15)
reference_images\I15.BMP (589878, 2007-01-15)
reference_images\I16.BMP (589878, 2007-01-15)
reference_images\I17.BMP (589878, 2007-01-15)
reference_images\I18.BMP (589878, 2007-01-15)
reference_images\I19.BMP (589878, 2007-01-15)
reference_images\I20.BMP (589878, 2007-01-15)
reference_images\I21.BMP (589878, 2007-01-15)
reference_images\I22.BMP (589878, 2007-01-15)
reference_images\I23.BMP (589878, 2007-01-15)
reference_images\I24.BMP (589878, 2007-01-15)
reference_images\i25.bmp (589878, 2007-01-26)
reference_images\metrics_values (0, 2014-02-11)
reference_images\metrics_values\FSIM.txt (21000, 2013-01-15)
reference_images\metrics_values\FSIMc.txt (21000, 2013-01-17)
reference_images\metrics_values\MSSIM.txt (21000, 2013-01-15)
reference_images\metrics_values\NQM.txt (23705, 2013-02-04)
reference_images\metrics_values\PSNR.txt (24444, 2013-01-24)
reference_images\metrics_values\PSNRHA.txt (24000, 2013-01-17)
reference_images\metrics_values\PSNRHMA.txt (24000, 2013-01-17)
reference_images\metrics_values\PSNRHVS.txt (24444, 2013-01-15)
reference_images\metrics_values\PSNRHVSM.txt (24445, 2013-01-15)
reference_images\metrics_values\PSNRc.txt (24000, 2013-01-23)
reference_images\metrics_values\SSIM.txt (21000, 2013-01-15)
reference_images\metrics_values\VIFP.txt (21000, 2013-01-15)
reference_images\metrics_values\VSNR.txt (24049, 2013-02-04)
... ...

TAMPERE IMAGE DATABASE 2013 TID2013, version 1.0 TID2013 is intended for evaluation of full-reference image visual quality assessment metrics. TID2013 allows estimating how a given metric corresponds to mean human perception. For example, in accordance with TID2013, Spearman correlation between the metric PSNR (Peak Signal to Noise Ratio) and mean human perception (MOS, Mean Opinion Score) is 0.69. Permission to use, copy, or modify this database and its documentation for educational and research purposes only and without fee is hereby granted, provided that this copyright notice and the original authors' names appear on all copies and supporting documentation. This database shall not be modified without first obtaining permission of the authors. The authors make no representations about the suitability of this database for any purpose. It is provided "as is" without express or implied warranty. In case of publishing results obtained by means of TID2013 please refer to the following paper (see file euvip_tid2013.pdf in the "papers\" direcory): [1] N. Ponomarenko, O. Ieremeiev, V. Lukin, K. Egiazarian, L. Jin, J. Astola, B. Vozel, K. Chehdi, M. Carli, F. Battisti, C.-C. Jay Kuo, "Color Image Database TID2013: Peculiarities and Preliminary Results", accepted to 4th Europian Workshop on Visual Information Processing EUVIP2013, Paris, France, June 10-12, 2013, 6p. The TID2008 contains 25 reference images and 3000 distorted images (25 reference images x 24 types of distortions x 5 levels of distortions). All images are saved in database in Bitmap format without any compression. File names are organized in such a manner that they indicate a number of the reference image, then a number of distortion's type, and, finally, a number of distortion's level: "iXX_YY_Z.bmp". For example, the name "i03_08_4.bmp" means the 3-rd reference image corrupted by the 8-th type of distortions with the 4-th level of this distortion. Similarly, the name "i12_10_1.bmp" means that this is the 12-th reference image corrupted by the 10-th type of distortion with the first level. "i17.bmp" means that this is non-distorted 17-th reference image. TABLE I. Types of distortion used in TID2008 ü Type of distortion 1 Additive Gaussian noise 2 Additive noise in color components is more intensive than additive noise in the luminance component 3 Spatially correlated noise 4 Masked noise 5 High frequency noise 6 Impulse noise 7 Quantization noise 8 Gaussian blur 9 Image denoising 10 JPEG compression 11 JPEG2000 compression 12 JPEG transmission errors 13 JPEG2000 transmission errors 14 Non eccentricity pattern noise 15 Local block-wise distortions of different intensity 16 Mean shift (intensity shift) 17 Contrast change 18 Change of color saturation 19 Multiplicative Gaussian noise 20 Comfort noise 21 Lossy compression of noisy images 22 Image color quantization with dither 23 Chromatic aberrations 24 Sparse sampling and reconstruction See [1] for a more detailed explanation. The file "mos.txt" contains the Mean Opinion Score for each distorted image. The file "mos_with_names.txt" contains the same information and filenames of the coressponding distorted images. The file "mos_std.txt" contains standard deviation of MOS for each distorted image. The MOS was obtained from the results of 971 experiments carried out by observers from five countries: Finland, France, Italy, Ukraine and USA (116 experiments have been carried out in Finland, 72 in France, 80 in Italy, 602 in Ukraine, and 101 in USA). Totally, the 971 observers have performed 524340 comparisons of visual quality of distorted images or 1048680 evaluations of relative visual quality in image pairs. Higer value of MOS (0 - minimal, 9 - maximal) corresponds to higer visual quality of the image. The following files contain values of some quality metrics calculated for the TID2008 images: "psnrc.txt" - peak signal to noise ratio; "psnr.txt" - peak signal to noise ratio calculated for the luminance component; "ssim.txt" - values of the SSIM metric [3]; "mssim.txt" - vaules of the MSSIM metric [4,2]; "psnrhvs.txt" - values of the PSNR-HVS metric [5]; "psnrhvsm.txt" - values of the PSNR-HVS-M metric [6]; "psnrha.txt" - values of the PSNRHA metric [7]; "psnrhma.txt" - values of the PSNRHMA metric [7]; "vifp.txt" - pixel domain version VIF [8,3]; "nqm.txt" - values of the NQM metric [9,3]; "wsnr.txt" - values of the WSNR metric [10,3]; "vsnr.txt" - values of the VSNR metric [11,3]; "fsim.txt" - values of the FSIM metric [12]; "fsimc.txt" - values of color version of FSIM metric [12]; [2] Matthew Gaubatz, "Metrix MUX Visual Quality Assessment Package: MSE, PSNR, SSIM, MSSIM, VSNR, VIF, VIFP, UQI, IFC, NQM, WSNR, SNR", http://foulard.ece.cornell.edu/gaubatz/metrix_mux/ [3] Z. Wang, A. Bovik, H. Sheikh, E. Simoncelli, "Image quality assessment: from error visibility to structural similarity", IEEE Transactions on Image Proc., vol. 13, issue 4, pp. 600-612, April, 2004. [4] Z. Wang, E. P. Simoncelli and A. C. Bovik, "Multi-scale structural similarity for image quality assessment," Invited Paper, IEEE Asilomar Conference on Signals, Systems and Computers, Nov. 2003. [5] K. Egiazarian, J. Astola, N. Ponomarenko, V. Lukin, F. Battisti, M. Carli, "New full-reference quality metrics based on HVS", CD-ROM Proceedings of the Second International Workshop on Video Processing and Quality Metrics, Scottsdale, USA, 2006, 4 p. [6] N. Ponomarenko, F. Silvestri, K. Egiazarian, M. Carli, J. Astola, V. Lukin "On between-coefficient contrast masking of DCT basis functions", CD-ROM Proc. of the Third International Workshop on Video Processing and Quality Metrics. - USA, 2007. - 4 p. [7] N. Ponomarenko, O. Eremeev, Lukin V., K. Egiazarian, M. Carli, "Modified image visual quality metrics for contrast change and mean shift accounting", Proceedings of CADSM, Polyana-Svalyava, 2011, pp. 305-311. [8] H.R. Sheikh.and A.C. Bovik, "Image information and visual quality," IEEE Transactions on Image Processing, Vol.15, no.2, 2006, pp. 430-444. [9] Damera-Venkata N., Kite T., Geisler W., Evans B. and Bovik A. "Image Quality Assessment Based on a Degradation Model", IEEE Trans. on Image Processing, Vol. 9, 2000, pp. 636-650. [10] T. Mitsa and K. Varkur, "Evaluation of contrast sensitivity functions for the formulation of quality measures incorporated in halftoning algorithms", ICASSP '93-V, pp. 301-304. [11] D.M. Chandler, S.S. Hemami, "VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio for Natural Images", IEEE Transactions on Image Processing, Vol. 16 (9), pp. 2284-22***, 2007. [12] L. Zhang, X. Mou, D. Zhang, "FSIM: a feature similarity index for image quality assessment", IEEE Transactions on Image Processing, vol. 20, No 5, 2011, pp. 2378--2386. The programs "spearman.exe" and "kendall.exe" calculate values of Spearman and Kendall rank correlations for entire set of the TID2008 images as well as for particular subsets given in the Table II. TABLE II. Subsets of TID2013 definded by default ü Type of distortion Noise Actual Simple Exotic New Color Full 1 Additive Gaussian noise + + + - - - + 2 Noise in color comp. + - - - - + + 3 Spatially correl. noise + + - - - - + 4 Masked noise + + - - - - + 5 High frequency noise + + - - - - + 6 Impulse noise + + - - - - + 7 Quantization noise + - - - - + + 8 Gaussian blur + + + - - - + 9 Image denoising + + - - - - + 10 JPEG compression - + + - - + + 11 JPEG2000 compression - + - - - - + 12 JPEG transm. errors - - - + - - + 13 JPEG2000 transm. errors - - - + - - + 14 Non ecc. patt. noise - - - + - - + 15 Local block-wise dist. - - - + - - + 16 Mean shift - - - + - - + 17 Contrast change - - - + - - + 18 Change of color saturation - - - - + + + 19 Multipl. Gauss. noise + + - - + - + 20 Comfort noise - - - + + - + 21 Lossy compr. of noisy images + + - - + - + 22 Image color quant. w. dither - - - - + + + 23 Chromatic aberrations - - - + + + + 24 Sparse sampl. and reconstr. - - - + + - + The command line is "spearman " or "kendall ". Command line examples: spearman mos.txt ssim.txt kendall psnr.txt psnr-hvs.txt An example of usage: kendall.exe mos.txt FSIMc.txt Noise : 0.722 Actual : 0.742 Simple : 0.792 Exotic : 0.651 New : 0.611 Color : 0.592 Full : 0.666 TABLE III. Ranking of compared metrics in accordance with Spearman correlation with MOS Rank Measure Spearman correlation 1 FSIMc 0.851 2 PSNR-HA 0.819 3 PSNR-HMA 0.813 4 FSIM 0.801 5 MSSIM 0.787 6 PSNRc 0.687 7 VSNR 0.681 8 PSNR-HVS 0.654 9 PSNR 0.***0 10 SSIM 0.637 11 NQM 0.635 12 PSNR-HVS-M 0.625 13 VIFP 0.608 14 WSNR 0.580 TABLE IV. Ranking of compared metrics in accordance with Kendall correlation with MOS Rank Measure Kendall correlation 1 FSIMc 0.667 2 PSNR-HA 0.***3 3 PSNR-HMA 0.632 4 FSIM 0.630 5 MSSIM 0.608 6 VSNR 0.508 7 PSNR-HVS 0.508 8 PSNRc 0.496 9 PSNR-HVS-M 0.482 10 PSNR 0.470 11 NQM 0.466 12 SSIM 0.4*** 13 VIFP 0.457 14 WSNR 0.446 We plan to regularly update the versions of this database. New versions will include new types of distortion and take into account results of additional experiments. We will highly appreciate authors of other metrics if they will inform us (please, mail to nikolay@ponomarenko.info) how to get executable files (e.g., Matlab codes) of their metrics. We guarantee that we will not pass them to other users and will include future results obtained for such metrics in analysis for our database.

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