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A Comparison of Still-Image Compression Standards and Proposed Methods for Improving Lossy Image Quality

A Comparison of Still-Image Compression Standards and Proposed Methods for Improving Lossy Image Quality. MDDSP Literature Survey Presentation Eric Heinen. Project Goals. Investigate existing methods for improving JPEG image quality Consider adapting these methods to JPEG2000

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A Comparison of Still-Image Compression Standards and Proposed Methods for Improving Lossy Image Quality

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  1. A Comparison of Still-Image Compression Standards and Proposed Methods for Improving Lossy Image Quality MDDSP Literature Survey Presentation Eric Heinen

  2. Project Goals • Investigate existing methods for improving JPEG image quality • Consider adapting these methods to JPEG2000 • Novel approaches? • Compare image quality of JPEG and JPEG2000 (with & without improvements) across • Image set • Compression ratios

  3. Joint Thresholding and Quantizer Selection for JPEG Encoding(M. Crouse and K. Ramchandran, 1997) • Optimize encoding without affecting decoding • Rate-Distortion optimization framework

  4. Improved JPEG Compression Using Human Visual System (HVS) Model(G. Sreelekha and P. S. Sathidevi, 2005) • Exploits contrast sensitivity of HVS • Sinusoid at given frequency requires certain amount of contrast to elicit a response • HVS is insensitive to very low and very high frequencies • Contrast Sensitivity Function (CSF) • CSF Thresholding • Discard DCT coefficients below CSF value

  5. Improved JPEG Compression Using Human Visual System (HVS) Model(G. Sreelekha and P. S. Sathidevi, 2005) • Also exploits masking property of HVS • Vision less sensitive to local variation in brighter regions • Compute luminance masking threshold based on block’s DC coefficient • DCT coefficients below this threshold discarded • Quantization after thresholding • different from JPEG standard • incompatible with JPEG standard decoder

  6. JPEG2000 vs. JPG • Arbitrary rectangular tile size allowed • Color space transformation can be • Lossless (YUV) • or lossy (YCbCr) • Discrete Wavelet Transform (DWT) • More sophisticated entropy encoding • Improvements to JPEG can be applied

  7. Image Quality Assessment • Full-reference image quality metrics (IQM) • Estimate DMOS • Convenient • Popular IQMs • Peak Signal to Noise Ratio (PSNR) • Universal Image Quality Index • Structural Similarity (SSIM)

  8. Statistical Evaluation of Recent IQMs(H. R. Sheikh, M. F. Sabir, and A. C. Bovik, 2006) • Image database • Set of distortions • JPEG, JPEG2000, White Noise, Gaussian Blur, simulated wireless channel • Collect mean opinion scores • 3 different performance metrics • RMSE between IQM score and DMOS after non-linear regression

  9. Questions?

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