An adaptive lighting correction method for matched-texture coding

Guoxin Jin; Thrasyvoulos N Pappas; David L. Neuhoff

doi:10.1109/ICASSP.2014.6853950

An adaptive lighting correction method for matched-texture coding

Guoxin Jin, Thrasyvoulos N Pappas, David L. Neuhoff

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

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.

Original language	English (US)
Title of host publication	2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2006-2010
Number of pages	5
ISBN (Print)	9781479928927
DOIs	https://doi.org/10.1109/ICASSP.2014.6853950
State	Published - Jan 1 2014
Event	2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy Duration: May 4 2014 → May 9 2014

Other

Other	2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Country/Territory	Italy
City	Florence
Period	5/4/14 → 5/9/14

Keywords

Dirichlet problem
Neumman problem
Poisson equation
structural texture similarity metric

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

Access to Document

10.1109/ICASSP.2014.6853950

Cite this

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title = "An adaptive lighting correction method for matched-texture coding",

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 = "Dirichlet problem, Neumman problem, Poisson equation, structural texture similarity metric",

author = "Guoxin Jin and Pappas, {Thrasyvoulos N} and Neuhoff, {David L.}",

year = "2014",

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note = "2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 ; Conference date: 04-05-2014 Through 09-05-2014",

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Jin, G, Pappas, TN & Neuhoff, DL 2014, An adaptive lighting correction method for matched-texture coding. in 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014., 6853950, Institute of Electrical and Electronics Engineers Inc., pp. 2006-2010, 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, Florence, Italy, 5/4/14. https://doi.org/10.1109/ICASSP.2014.6853950

An adaptive lighting correction method for matched-texture coding. / Jin, Guoxin; Pappas, Thrasyvoulos N; Neuhoff, David L.
2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 2006-2010 6853950.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - An adaptive lighting correction method for matched-texture coding

AU - Jin, Guoxin

AU - Pappas, Thrasyvoulos N

AU - Neuhoff, David L.

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N2 - 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.

AB - 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.

KW - Dirichlet problem

KW - Neumman problem

KW - Poisson equation

KW - structural texture similarity metric

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Y2 - 4 May 2014 through 9 May 2014

ER -

An adaptive lighting correction method for matched-texture coding

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Keywords

ASJC Scopus subject areas

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