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.
How to test your metric? Step 1. Download the TID2013. Step 2. Calculate values of your metric
for each distorted image of TID2013. Step 3. Use included software
("spearman.exe" or "kendall.exe") for calculate a correlation between your metric and MOS.
In case of publishing results obtained by means of TID2013 please
refer to one of following paper:
 N. Ponomarenko, L. Jin, O. Ieremeiev, V. Lukin, K. Egiazarian, J. Astola, B. Vozel, K. Chehdi, M. Carli, F. Battisti, C.-C. Jay Kuo, Image database TID2013: Peculiarities, results and perspectives, Signal Processing: Image Communication, vol. 30, Jan. 2015, pp. 57-77.
 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,
Proceedings of 4th Europian Workshop on Visual Information Processing EUVIP2013, Paris,
France, June 10-12, 2013, pp. 106-111.
 N. Ponomarenko, O. Ieremeiev, V. Lukin, K. Egiazarian, L. Jin, J. Astola, B. Vozel, K. Chehdi, M. Carli, F. Battisti, C.-C. Jay Kuo, A New Color Image Database TID2013: Innovations and Results, Proceedings of ACIVS, Poznan, Poland, Oct. 2013, pp. 402-413.
WinRAR archive with TID2013 (~913 MB):
The TID2013 contains 25 reference images and 3000 distorted images
(25 reference images x 24 types of distortions x 5 levels of distortions).
Reference images are obtained by cropping from Kodak Lossless True
Color Image Suite.
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".
The file "mos.txt" contains the Mean Opinion Score 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, MSE of each score
is 0.018) corresponds to higer visual quality of the image.
Ranking of compared metrics in accordance Ranking of compared metrics in accordance
with Spearman correlation with MOS with Kendall correlation with MOS
Rank Measure Spearman correlation Rank Measure Kendall correlation
1 FSIMc 0.851 1 FSIMc 0.667
2 PSNR-HA 0.819 2 PSNR-HA 0.643
3 PSNR-HMA 0.813 3 PSNR-HMA 0.632
4 FSIM 0.801 4 FSIM 0.630
5 MSSIM 0.787 5 MSSIM 0.608
6 PSNRc 0.687 6 VSNR 0.508
7 VSNR 0.681 7 PSNR-HVS 0.508
8 PSNR-HVS 0.654 8 PSNRc 0.496
9 PSNR 0.640 9 PSNR-HVS-M 0.482
10 SSIM 0.637 10 PSNR 0.470
11 NQM 0.635 11 NQM 0.466
12 PSNR-HVS-M 0.625 12 SSIM 0.464
13 VIFP 0.608 13 VIFP 0.457
14 WSNR 0.580 14 WSNR 0.446
Types of distortion used in TID2013
N 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
The following files contain values of some quality metrics calculated for
the TID2013 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 ;
"mssim.txt" - vaules of the MSSIM metric [4,2];
"psnrhvs.txt" - values of the PSNR-HVS metric ;
"psnrhvsm.txt" - values of the PSNR-HVS-M metric ;
"psnrha.txt" - values of the PSNRHA metric ;
"psnrhma.txt" - values of the PSNRHMA metric ;
"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 ;
"fsimc.txt" - values of color version of FSIM metric ;
 Matthew Gaubatz, "Metrix MUX Visual Quality Assessment Package: MSE,
PSNR, SSIM, MSSIM, VSNR, VIF, VIFP, UQI, IFC, NQM, WSNR, SNR",
 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.
 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.
 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.
 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.
 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.
 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.
 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.
 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.
 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. 2284-2298, 2007.
 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 TID2013 images as well
as for particular subsets given in the following Table:
Subsets of TID2013 definded by default
¹ 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 data1 data2" or "kendall data1 data2".
Command line examples:
spearman mos.txt ssim.txt
kendall mos.txt dctune.txt
spearman linlab.txt xyz.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
We plan to regularly update the versions of this database. New versions
will include new types of distortion and take into account results of
We will highly appreciate authors of other metrics if they will inform
us (please, mail to email@example.com) 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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Last changed: 2015-03-23.