1. EE368B1 A Comparison of Quality Metrics for JPEG Images Feng Xiao Fall 2000

2. EE368B2 Motivation Compare performance of different image metrics for JPEG images with subjective measurement –Blocking is the dominant artifact in JPEG images (or other block- based coding), especially at low-bit-rate –Post-processing may incur blurring when reducing blocking –Need a good metrics

3. EE368B3 Candidate Metrics RMSE ( root-mean-square error ) BMR ( block-to-mask ratio, Liu 1997 ) EOBD ( effect-of-block-distortion, Eskicioglu 1995 ) MIX (RMSE + BMR) –RMSE is pixel-based, and BMR is block-based, combination may be more robust

4. EE368B4 BMR: I Compute the block difference 6789 1 2 Block Border

5. EE368B5 BMR: II Include the perceptual effects whereis the just-noticeable difference 50 is a weighted ratio

6. EE368B6 BMR: III Separate the blocking and blurring measure OBMR(i,j): BMR in the original image PBMR(i,j): BMR in the processed image. –a) PBMR(i,j) > OBMR(i,j). Block(i,j) in processed image is more blocking than that of the original image. –b) PBMR(i,j) <= OBMR(i,j). Block(i,j) is blurred in processed image. –blocking strength = mean(|OBMR(i,j)-PBMR(i,j)|) for set a –blurring strength = mean(|OBMR(i,j)-PBMR(i,j)|) for set b

7. EE368B7 BMR: IV Construct the single BMR BMR= blocking strength + blurring strength

8. EE368B8 BMR: V JPEG quality Strength Size of smoothing filter

9. EE368B9 EOBD

10. EE368B10 Experiments Click on the image with the worst quality JPEG JPEG with Filtering (3x3) JPEG with de-block

11. EE368B11 Experiments (cont.) Each experiment has18x3 images: –18 JPEG images at quality levels 5~40 (bits.25~.80 bpp) –18 smoothed (3x3) JPEG images –18 de-blocked JPEG images (Chou’s 1995) Repeat 4 times 2 subjects, 2 image sets (‘lena’ & ‘einstein’)

12. EE368B12 Results: Comparison Mean Rank Error RMSE BMRMIXEOBD Rank Error for Image i: E i = | S i – R i |, where S i is the subjective rank of image I, R i is the rank derived from metrics

13. EE368B13 Results: Post-processing Bit Rate (bpp) Improvement (rank order)

14. EE368B14 Results: RMSE vs. Subjective Subjective Rank Order RMSE

15. EE368B15 Results: BMR vs. Subjective Subjective Rank Order BMR

16. EE368B16 Results: EOBD vs. Subjective EOBD Subjective Rank Order

17. EE368B17 Results: MIX vs. Subjective MIX Subjective Rank Order

18. EE368B18 Conclusion MIX is the best metrics as tested –It takes both pixel-based metrics (RMSE) and block-based metrics (BMR) into consideration. Both smooth (3x3) and de-block (chou’s) show improvement for low bit-rate.