eurocon2009 khryashchev

1EUROCON 2009, May 21, Saint-Peterburg

NO-REFERENCE QUALITY ASSESSMENT OF WAVELET-COMPRESSED IMAGES

Vladimir Khryashchev

Yaroslavl State UniversityRussia

2EUROCON 2009, May 21, Saint-Peterburg

Outline

• Image compression: JPEG vs. JPEG2000

• Image quality assessment: from PSNR to No-Reference estimation

• Algorithm description

• Results

• Conclusions

3

Image compression standard history

• JPEG – 1994 ISO/IEC 10918-1, ITU-T.Rec.T.81

• JPEG 2000 – December 2000ISO/IEC 15444-1

The experts decided to depart from the block based DCT coding used byexisting JPEG and MPEG standards in favor of wavelet based compressionwhich delivered better quality.

EUROCON 2009, May 21, Saint-Peterburg

4

JPEG Artifacts

Original Lenna Image Lenna with JPEG compression (ratio K=40)

8x8 block structure !!!

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5

JPEG2000 Artifacts

Original Lenna Image

Blurring !!!

Lenna with JPEG2000 compression (ratio K=80)

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6

JPEG2000 Artifacts

Original Lenna Image

Ringing !!!

Lenna with JPEG2000 compression (ratio K=80)

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JPEG vs JPEG2000 Comparison (Classical)

0 10 20 30 40 50 6024

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28

30

32

34

36

38

40

K

PS

NR

, dB

JPEG2000JPEG

JPEG without deblocking, JPEG 2000 Kakadu v. 6.0

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JPEG vs JPEG2000 Comparison (Classical)

JPEG 2000 delivers about 20% better compression than JPEG. And, at more extreme compression ratios, JPEG 2000 delivers significantly better quality.

Another key benefit of JPEG 2000 is that it supports both losslessand lossy compression in a single codec – a very desirable feature incertain applications such as medical imaging.

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JPEG vs JPEG2000 Comparison (Modern)

JPEG with deblocking, JPEG 2000, SPIHT, AGU (DCT 32x32)

N.N. Ponomarenko, K.O. Egiazarian, V.V. Lukin, J.T. Astola, High-Quality DCT-Based Image Compression

Using Partition Schemes, IEEE Signal Processing Letters , Vol. 14, Issue 2, February, 2007, pp. 105-108.

http://ponomarenko.info/agu.htm

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Motion JPEG2000 Standard for Digital Cinema

In Motion JPEG 2000 each frame is coded individually. Intra-frame coding allows for random access and reduced complexity. In MPEG the encoding uses a series of frames – inter-frame coding. This allows for improved compression efficiency but the coding technique is more complex.

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From MSE and PSNR to modern image quality assessment

Z. Wang and A.C. Bovik, "Mean squared error: Love it or leave it? - A new look at signal fidelity measures", IEEE Signal Processing Magazine, Vol: 26 No: 1, Page(s): 98-117, January 2009.

N. Ponomarenko, F. Battisti, K. Egiazarian, J. Astola, V. Lukin "Metrics performance comparison for color image database", Fourth international workshop on video processing and quality metrics for consumer electronics, Scottsdale, Arizona, USA. Jan. 14-16, 2009, 6 p.

Introduction paper

Detailed analysis for 18 metricsand 17 types of distortions

More than 20 new full-reference metrics

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The problem formulation

create a no-reference (working without original image) metrics for estimation quality of JPEG2000 compression images

Quality ?

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No-reference Algorithm for JPEG2000

Based on statistical model of the wavelet coefficient’s magnitude proposed by Simoncelli (1997) and Bovik at al (2002) algorithm of quality estimation.

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Joint histograms for one subband of Lenna image

original K=3,29

K=10,26 K=42,11

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Partition of the (P, C) space into quadrants

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Quality estimation calculation

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Quality estimation calculation

No-reference image quality estimation (NIQE2000)from [0, 100] interval

where the weights ω are learned by minimizing quality prediction error over the training set

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MOS estimation for JPEG2000 images

Visual experiment in Yaroslavl State University10 test images, 7 compression ratio for JPEG2000, 100 peoples.

ITU-R BT.500-11 methodology for DMOS calculations

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Subband labels

1H

1V 23H

4

5H

5V 6

7H

7V 8

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Subband visualization

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Parameters optimization

Obtained algorithm parameters’ values for finest and second-finest scales are shown in this table. Last two scales of the wavelet transformation were not used since quantization process has little effect on them.

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Visual Results

Original Image K=17, PSNR=36,61 dB,UQI=0,60, NIQE2000=60,12

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Visual Results

K=100, PSNR=28,97 dB,UQI=0,37, NIQE2000=31,61

K=50, PSNR=31,96 dB,UQI=0,46, NIQE2000=35,62

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NIQE2000 with PSNR

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Correlation between MOS and objective estimations

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Conclusions

NIQE2000 criteria can be successfully used for quality assessment of images compressed with JPEG2000 algorithm.

The correlations between NIQE2000 and MOS is close to PSNR-MOS, but NIQE2000 is no-reference estimation with very important for practical tasks.

Another no-reference quality assessment algorithms for JPEG2000 can be done by estimation ringing and blurring artifacts separately and after combining them to the new quality metrics.

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Real-Life JPEG2000 Yaroslavl Image Quality Estimation

NIQE = 100

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Real-Life JPEG2000 Yaroslavl Image Quality Estimation

NIQE = 100

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Real-Life JPEG2000 Yaroslavl Image Quality Estimation

NIQE = 100

30EUROCON 2009, May 21, Saint-Peterburg

Real-Life JPEG2000 Yaroslavl Image Quality Estimation

NIQE = 100

31EUROCON 2009, May 21, Saint-Peterburg

Yaroslavl 1000 anniversary (1010-2010)

You are Welcome !!!

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Thank you for your attention !!!