1 / 21

Tuning Baseline JPEG Encoding for Individual Images

Tuning Baseline JPEG Encoding for Individual Images. Chien-An Lai Changchuan Yu EE398A Final Project Mar 15 th 2007 . Outline. Motivation Baseline JPEG Optimization Algorithm with baseline JPEG compliance Results Conclusion. Motivation. Flexibility of baseline JPEG – Q and H tables

ayanna
Download Presentation

Tuning Baseline JPEG Encoding for Individual Images

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Tuning Baseline JPEG Encoding for Individual Images Chien-An Lai Changchuan Yu EE398A Final Project Mar 15th 2007

  2. Outline • Motivation • Baseline JPEG • Optimization Algorithm with baseline JPEG compliance • Results • Conclusion

  3. Motivation • Flexibility of baseline JPEG – Q and H tables •  what gain could we get from changing the tables? • A ’97 algorithm revisited in ’07 • Joint implementation of different optimizing techniques • R-D optimized quantizer selection • R-D optimal thresholding • Optimal Huffman encoding • Compare the best baseline JPEG to state-of-the-art JPEG2000

  4. Baseline JPEG • Block-Diagram DCT (8*8) Quantizer Q matrix (8*8) Entropy Coding (Huffman) 101101… Bit sequence 8*8 blocks

  5. Modified baseline JPEG • Block-Diagram Entropy Coding DCT (8*8) Quantizer Threshold T matrix 101101… Bit sequence Q T H 8*8 blocks Q matrix Selection Optimal Thresholding Huffman table Customization Image-adaptive optimization

  6. Algorithm Overview Entropy Coding DCT (8*8) Quantizer Threshold T matrix 101101… Bit sequence Q T H 8*8 blocks Q matrix Selection Optimal Thresholding Huffman table Customization Loop ‘til converge Image-adaptive optimization

  7. Algorithm - Q • For n=1:64 • For q=1:255 • End • End • A fast algorithm is needed, or it’s equivalent to jpeg encoding 255*64 pictures for one single Q search!

  8. Algorithm - Thresholding find which k* is optimal for minimal cost and backtracking from k* to find the T coefficients. This is equivalently the optimal value for 2^63 thresholding combinations.

  9. Algorithm – Huffman Table • Optimization under the constraint of baseline JPEG format • Reordering of Huffman table according to the real statistics table=[... 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 4 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 5 5 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 6 6 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 7 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 8 10 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 0 9 16 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1 0 0 10 16 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1 1 1 1 4 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 6 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1 3 7 1 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 1 4 9 1 1 1 1 1 0 1 1 0 0 0 0 0 0 0 0 1 5 11 1 1 1 1 1 1 1 0 1 1 0 0 0 0 0 0 1 6 16 1 1 1 1 1 1 1 1 1 0 0 0 0 1 0 0 Re-ordering 2-D symbol run cat code length

  10. How we did the testing • Matlab modeling of baseline JPEG • An accurate model, with everything but headers • Slow! • Baseline JPEG rate-psnr using scaling of Q table • JPEG2000 rate-psnr using rate-constrained Jasper* coder • Mostly run on Scien Lab machines *http://www.ece.uvic.ca/~mdadams/jasper/

  11. Results1 – bridge512x512

  12. Results1 32.5dB, 2.0 bits/pixel 32.3dB, 1.4 bits/pixel

  13. Results1 Q optimized = 11 29 33 31 41 33 43 41 37 33 31 37 39 41 41 57 33 33 37 37 41 41 45 49 35 35 37 37 43 43 53 85 35 41 41 41 43 57 75 111 39 41 43 45 57 83 95 101 37 47 51 53 75 77 93 81 47 47 57 65 97 95 83 87 Q baseline = 15 10 10 15 23 38 49 58 11 11 13 18 25 55 57 52 13 12 15 23 38 54 66 53 13 16 21 28 49 83 76 59 17 21 35 53 65 104 98 73 23 33 52 61 77 99 108 88 47 61 74 83 98 115 114 96 69 88 90 93 107 95 98 94

  14. Results2 – 512x512

  15. Results2 – Halfdome top 32.8dB, 0.8 bits/pixel 32.9dB, 1.0 bits/pixel

  16. Results2 – Halfdome top 27.9dB, 0.8 bits/pixel 26.5dB, 0.8 bits/pixel

  17. Results2 Q optimized = 46 19 19 17 19 15 21 23 23 19 19 19 19 21 21 27 20 19 17 19 19 21 25 27 19 19 17 21 21 21 19 27 15 19 17 19 19 21 21 23 19 17 19 17 21 19 21 25 17 21 21 19 21 25 23 35 21 19 21 21 19 23 25 59 Q baseline = 8 6 5 8 12 21 26 31 6 6 7 10 13 30 31 28 7 7 8 12 21 29 36 29 7 9 11 15 26 45 41 32 9 11 19 29 35 56 53 40 12 18 28 33 42 54 58 47 25 33 40 45 53 62 62 52 37 47 49 51 58 52 53 51

  18. Result – scaling effects 256x256, halfdome 512x512, halfdome

  19. Result – it does not always work peppers512x512

  20. Conclusion • Optimization of Q and H tables can result in significant gain, compared to recommended tables • Most gain from Q optimization • Huffman optimization contributes some performance gain • Optimal Thresholding produces little gain • At a cost of thousands times of computation effort • 1+ hours of searching in matlab, on Scien Lab machines • No guarantee for global optimization • JPEG2000 is a far superior winner, hands down • Encoding takes only mini-seconds • Precise control of bit rate

  21. References • [1] G. K. Wallace, "The JPEG still picture compression standard," Communications of the ACM,  vol. 34, no. 4, April 1991. • [2] M. Crouse and K. Ramchandran, "Joint thresholding and quantizer selection for transform image coding: entropy-constrained analysis and applications to baseline JPEG", IEEE Transactions on Image Processing, vol. 6, no. 2, February 1997. • [3] K. Ramchandran and M. Vetterli, “Rate-distortion optimal fast thresholding with complete JPEG/MPEG decoder compatibility,” IEEE Trans. Image Processing, vol. 3, pp. 700–704, Sept. 1994.

More Related