JPEG XR objective and subjective evaluations

Rate-distortion p erformance evaluation of JPEG-XR Objective results and proposed methodology for subjective quality assessment Francesca De Simone, Frederic Dufaux, Touradj Ebrahimi JPEG XR Camera Raw coding AHG meeting 18-19 February 2009, Tokyo, Japan

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[object Object],[object Object],[object Object],[object Object],QA and codec performance evaluation ,[object Object],Original picture Output picture JPEG or JPEG 2000 or JPEG XR HUMAN SUBJECT (subjective QA) or FR METRIC (objective QA)

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[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Our previous contributions

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Test Material – 24 bpp pictures (sample pictures from Thomas Richter dataset, 2 different spatial resolutions: 3888x2592, 2592x3888 ) (sample pictures from Microsoft dataset, 6 different spatial resolutions: 4064x2704, 2268x1512, 2592x1944, 2128x2832, 2704x3499, 4288x2848)

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Codecs and configuration parameters

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Codecs and configuration parameters

Metric 1: Maximum Pixel Deviation (L inf ) L inf R = max [abs(Im aR (x,y)-Im bR (x,y))] ,[object Object],[object Object],[object Object],[object Object],L inf G = max [abs(Im aG (x,y)-Im bG (x,y))] L inf B = max [abs(Im aB (x,y)-Im bB (x,y))] (L inf  [0,1])

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Metric 2: single channel PSNR

Metric 3: PSNR weighted average (WPSNR) WPSNR = w 1 PSNR 1 + w 2 PSNR 2 + w 3 PSNR 3 ,[object Object],[object Object],[object Object],[object Object]

Metric 3: PSNR weighted average (WPSNR_MSE) WPSNR_MSE ,[object Object],[object Object],[object Object],[object Object]

Metric 3: PSNR weighted average (WPSNR_PIX) WPSNR_PIX ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

[object Object],Metric 4: Mean SSIM (MSSIM) (I) ,[object Object],[object Object],[1] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “ Image Quality Assessment: From Error Measurement to Structural Similarity” (2004). ,[object Object],[object Object]

Metric 4: Mean SSIM (MSSIM) (II) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],(C 3 =constant)

Metric 4: Mean SSIM (MSSIM) (III) ,[object Object],[object Object],[object Object],[object Object],[object Object],(MSSIM  [0,1])

Metric 5: Visual Information Fidelity – Pixel (VIF-P) (I) ,[object Object],[2] H. R. Sheikh, A. C. Bovik “Image Information And Visual Quality” (2004). ,[object Object],Natural image (source) Channel (distortion) HVS HVS C F E ,[object Object],[object Object]

Metric 5: Visual Information Fidelity – Pixel (VIF-P) (II) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],(VIF  [0,1] and VIF>1 if the test image is enhanced version of the original )

Metric 6: PSNR-HVS-M (I) Block 8x8 of distorted image Block 8x8 of original image DCT of difference between pixel values Reduction by value of contrast masking MSE H calculation of the block [3] N. Ponomarenko, F. Silvestri, K. Egiazarian, M.Carli, J. Astola, and V. Lukin, “ On between-coefficient contrast masking of DCT basis functions” (2007). ,[object Object],[object Object],[object Object]

Metric 6: PSNR-HVS-M (II) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Metric 7: DC Tune [4] A. B. Watson, A. P. Gale, J. A. Solomon, and A. J. Ahumada JR., “ DCTune: A Techinque For Visual Optimization Of DCT Quantization Matrices For Individual Images” (1994). ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Selected results 4:4:4 – JPEG XR vs JPEG2000 vs JPEG Average over image dataset of PSNR values on R component: bpp (bits/pixel) bpp (bits/pixel) bpp (bits/pixel) on G component: on B component:

Average over image dataset of PSNR values on Y’ component: on Cb component: on Cr component: bpp (bits/pixel) bpp (bits/pixel) bpp (bits/pixel) Selected results 4:4:4 – JPEG XR vs JPEG2000 vs JPEG

Average over image dataset of WPSNR values on Y’CbCr components: on RGB components: bpp (bits/pixel) bpp (bits/pixel) Selected results 4:4:4 – JPEG XR vs JPEG2000 vs JPEG

Average over image dataset of WPSNR-MSE values on Y’CbCr components: on RGB components: bpp (bits/pixel) bpp (bits/pixel) Selected results 4:4:4 – JPEG XR vs JPEG2000 vs JPEG

Average over image dataset of WPSNR-PIX values on Y’CbCr components: on RGB components: bpp (bits/pixel) bpp (bits/pixel) Selected results 4:4:4 – JPEG XR vs JPEG2000 vs JPEG

Average over image dataset of MSSIM values on Y’ component: on Cb component: on Cr component: bpp (bits/pixel) Selected results 4:4:4 – JPEG XR vs JPEG2000 vs JPEG

Average over image dataset of VIF-P values on Y’ component only: bpp (bits/pixel) Selected results 4:4:4 – JPEG XR vs JPEG2000 vs JPEG

Average over image dataset of PSNR values (one level POT) on R component: on G component: on B component: bpp (bits/pixel) bpp (bits/pixel) bpp (bits/pixel) Selected results 4:4:4 – different JPEG XR implem.

Average over image dataset of PSNR values (two levels POT) on R component: on G component: on B component: bpp (bits/pixel) bpp (bits/pixel) bpp (bits/pixel) Selected results 4:4:4 – different JPEG XR implem.

Average over image dataset of PSNR values (one level POT) on Y component: on Cb component: on Cr component: bpp (bits/pixel) bpp (bits/pixel) bpp (bits/pixel) Selected results 4:4:4 – different JPEG XR implem.

Average over image dataset of PSNR values (two levels POT) on Y component: on Cb component: on Cr component: bpp (bits/pixel) bpp (bits/pixel) bpp (bits/pixel) Selected results 4:4:4 – different JPEG XR implem.

Average over image dataset of WPSNR_MSE values bpp (bits/pixel) bpp (bits/pixel) one level POT: two levels POT: Selected results 4:4:4 – different JPEG XR implem.

Average over image dataset of MSSIM values (one level POT) on Y component: on Cb component: on Cr component: bpp (bits/pixel) Selected results 4:4:4 – different JPEG XR implem.

Average over image dataset of MSSIM values (two levels POT) on Y component: on Cb component: on Cr component: bpp (bits/pixel) Selected results 4:4:4 – different JPEG XR implem.

[object Object],Proposed methodology (I) Reference Image Test Image ,[object Object],[object Object],[object Object],[object Object]

Proposed methodology (II) ,[object Object]

Proposed methodology (III) ,[object Object],Rating window (Continuous Quality Scale )

Proposed methodology (IV) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Proposed methodology (V) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Test conditions ,[object Object],[object Object],[object Object],[object Object],[object Object]

Preliminary results (I) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Content q=40 (T1) q=50 (T2) q=58 (T3) q=66 (T4) q=76 (T5) q=82 (T6) q=90 (T7) Cont. 1 0.9 0.64 0.46 0.34 0.22 0.18 0.13 Cont. 2 0.15 0.1 0.07 0.05 0.04 0.03 0.02 Cont. 3 0.9 0.61 0.43 0.31 0.19 0.15 0.1 Cont. 4 0.65 0.44 0.31 0.22 0.13 0.09 0.06

Preliminary results (II) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Acknowledgement ,[object Object],[object Object]

Thank you for your attention! Questions?

JPEG XR objective and subjective evaluations

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