1 / 10

Compound Coding

Compound Coding. Mark Kalman Isaac Keslassy Daniel Wang 12/6/00. Outline. Motivating Compound Coding Classification Algorithms Work from the Literature Spatial DCT-Based Methods Wavelets Our DCT Codebook Method Comparison Smoothing An Example. At 1bit/pel:

elroy
Download Presentation

Compound Coding

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. Compound Coding Mark Kalman Isaac Keslassy Daniel Wang 12/6/00

  2. Outline • Motivating Compound Coding • Classification Algorithms • Work from the Literature • Spatial • DCT-Based Methods • Wavelets • Our DCT Codebook Method • Comparison • Smoothing • An Example

  3. At 1bit/pel: Median graphics PSNR = 31dB Median text PSNR = 19.5 dB Different properties => different coding Motivating Compound Coding

  4. Past Work (1) • Spatial Domain Algorithms • Chen (1990) : block variance • Bones et al (1990) : edges (Sobel filter) • DCT-Based Algorithms • Chaddha et al (1995) : DCT-18 Absolute-Sum • Konstantinides (2000) : DCT Bit Rate

  5. Past Work (2) • Wavelet-based Algorithms • c2goodness of fit to Laplacian • similar to MSE • “discreteness” of distribution • concentration of data in peaks

  6. Our DCT Codebook Scheme • DCT coefficient values are differently distributed in text and graphic regions • Each distribution is given by a codebook histogram graphics text Distribution for DCT coefficient (2,1)

  7. The Algorithms Compared

  8. Smoothing Classification Algorithm Non-linear Smoothing Linear Smoothing

  9. An Example Uniform Coding .83 bits/pel Compound Coding .81 bits/pel

  10. Conclusion • Text and graphics have different characteristics • Many methods of classifying blocks • Spatial, DCT, Wavelets, DCT Codebooks • Smoothing/post-processing • Our methods compare favorably

More Related