Title :
An adaptive lighting correction method for matched-texture coding
Author :
Guoxin Jin ; Pappas, Thrasyvoulos N. ; Neuhoff, David L.
Author_Institution :
EECS Dept., Northwestern Univ., Evanston, IL, USA
Abstract :
Matched-Texture Coding is a novel image coder that utilizes the self-similarity of natural images that include textures, in order to achieve structurally lossless compression. The key to a high compression ratio is replacing large image blocks with previously encoded blocks with similar structure. Adjusting the lighting of the replaced block is critical for eliminating illumination artifacts and increasing the number of matches. We propose a new adaptive lighting correction method that is based on the Poisson equation with incomplete boundary conditions. In order to fully exploit the benefits of the adaptive Poisson lighting correction, we also propose modifications of the side-matching (SM) algorithm and structural texture similarity metric. We show that the resulting matched-texture algorithm achieves better coding performance.
Keywords :
Poisson equation; data compression; image coding; image matching; image texture; Poisson equation; SM algorithm; adaptive lighting correction method; illumination artifacts; image coder; lossless compression; matched texture coding; natural images; side matching; structural texture similarity metric; Boundary conditions; Encoding; Foot; Image coding; Lighting; Measurement; Poisson equations; Dirichlet problem; Neumman problem; Poisson equation; structural texture similarity metric;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
DOI :
10.1109/ICASSP.2014.6853950