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Enhancements to JPEG-LS Prediction Scheme for Improved Image Compression Performance

This study, presented by Chia-Chun Wu, explores enhancements to the JPEG-LS prediction scheme aimed at improving predictive accuracy and compression efficiency. The authors, S. Bedi, E. A. Edirisinghe, and G. Grecos, introduce modifications to the existing prediction model, showcasing experimental results that demonstrate a reduction in predictive mean squared error (PMSE) by up to 15%. The research also discusses how to dynamically adjust thresholds T1 and T2 based on image characteristics, providing valuable insights for achieving optimal compression settings.

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Enhancements to JPEG-LS Prediction Scheme for Improved Image Compression Performance

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  1. Improvements to the JPEG-LS prediction scheme Authors:S. Bedi, E. A. Edirisinghe, and G. Grecos Source : Image and Vision Computing. Vol. 22, No. 1, 2004, pp. 9-14 Speaker:Chia-Chun Wu (吳佳駿) Date : 2004/09/08

  2. Outline • Introduction to JPEG-LS • JPEG-LS prediction scheme • Improvements JPEG-LS prediction scheme • Experimental results • Conclusions • Comments

  3. Determine predictive value for x with prediction scheme Compute difference = x - Encode using entropy coding e Introduction to JPEG-LS Pixel value xin original image

  4. JPEG-LS prediction scheme  JPEG-LS predictive template

  5. JPEG-LS prediction scheme Horizontal edge Vertical edge

  6. JPEG-LS prediction scheme Vertical edge Horizontal edge

  7. JPEG-LS prediction scheme

  8. Improvements JPEG-LS Diagonal edge T1=20, T2=0 Diagonal edge T1=20, T2=0

  9. Experimental results  Predictive mean squared error N = 9

  10. Experimental results Table 1 PMSE values and lossless compression ratios of all test images, when compressed using JPEG-LS

  11. Experimental results Fig. 1. Performance at T1 = 11

  12. Experimental results Fig. 2. Performance at T1 = 19

  13. Experimental results Fig. 3. Optimum performance graphs

  14. Experimental results Table 2 Optimum performance and settings for proposed algorithm

  15. Experimental results Fig. 4. Predictive error images (a) using JPEG-LS, (b) using proposed scheme

  16. Conclusions • It maintains the low complexity requirement of JPEG-LS standard. • The proposed a modifications reduce the PMSE up to 15%.

  17. Comments • 如何根據影像不同的特性，動態的去調整門檻值T1及T2？ • 是否可以利用統計分析的方法，去找出適用於一般影像的門檻值T1及T2？

  18. Sample images Lena Baboon

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