Matched-texture coding for structurally lossless compression

Guoxin Jin*, Yuanhao Zhai, Thrasyvoulos N Pappas, David L. Neuhoff

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations


We propose a new texture-based compression approach that relies on new texture similarity metrics and is able to exploit texture redundancies for significant compression gains without loss of visual quality, even though there may visible differences with the original image (structurally lossless). Existing techniques rely on point-by-point metrics that cannot account for the stochastic and repetitive nature of textures. The main idea is to encode selected blocks of textures - as well as smooth blocks and blocks containing boundaries between smooth and/or textured regions - by pointing to previously occurring (already encoded) blocks of similar textures, blocks that are not encoded in this way, are encoded by a baseline method, such as JPEG. Experimental results with natural images demonstrate the advantages of the proposed approach.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Number of pages4
StatePublished - Dec 1 2012
Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
Duration: Sep 30 2012Oct 3 2012

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


Other2012 19th IEEE International Conference on Image Processing, ICIP 2012
Country/TerritoryUnited States
CityLake Buena Vista, FL


  • blending
  • direct block matching
  • side-matching
  • structural similarity metric

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems


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