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A Comparison of Quality Metrics for JPEG Images

Feng Xiao

Fall 2000

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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

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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

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BMR: I• Compute the block difference

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8

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Block Border

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BMR: II

• Include the perceptual effects

),(

),(log50),(

jiL

jiLjiBMR

JND

),( jiLJNDwhere is the just-noticeable difference

50 is a weighted ratio

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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

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BMR: IV

• Construct the single BMR

BMR= blocking strength + blurring strength

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BMR: V

JPEG quality

Str

engt

h

Str

engt

h

Size of smoothing filter

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EOBD

2)]1,(),([),(

2)],1(),([),(

2/1)]},(()],([{

NmfNmfNmf

nMfnMfnMfwith

NmfEnMfEEOBD

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ExperimentsClick on the image with the worst quality

JPEG JPEG withFiltering (3x3)

JPEG withde-block

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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’)

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Results: ComparisonM

ean

Ran

k E

rror

RMSE BMR MIX EOBD

Rank Error for Image i:Ei= | Si – Ri |, where Si is the subjective rank of image I, Ri is the rank derived from metrics

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Results: Post-processing

Bit Rate (bpp)

Impr

ovem

ent (

rank

ord

er)

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Results: RMSE vs. Subjective

Subjective Rank Order

RMSE

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Results: BMR vs. Subjective

Subjective Rank Order

BMR

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Results: EOBD vs. Subjective

EOBD

Subjective Rank Order

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Results: MIX vs. Subjective

MIX

Subjective Rank Order

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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.