A study of bias correction methods for enhancing median edge detector prediction

Haijiang Tang; Sei Ichiro Kamata; Kazuyuki Tsuneyoshi

doi:10.1109/MMSP.2005.248614

A study of bias correction methods for enhancing median edge detector prediction

Haijiang Tang^*, Sei Ichiro Kamata, Kazuyuki Tsuneyoshi

^*Corresponding author for this work

Graduate School of Information, Production and Systems

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

1 Citation (Scopus)

Abstract

In this paper, we present three novel lossless compression approaches for gray-scale continuous tone natural image. Our methods enhance the median edge detector (MED), which is the core part of JPED-LS algorithm, by reducing the entropy of the prediction error via adaptive regression. These modified predictors improve the prediction accuracy by reducing the negative effect due to MED's oversimplified edge orientation detection. The experimental results show that our approaches achieve evidently better performance than MED with only neglectable increasing of computational complexity and without introduce extra pixels into the causal template.

Original language	English
Title of host publication	2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005
DOIs	https://doi.org/10.1109/MMSP.2005.248614
Publication status	Published - 2006 Dec 1
Event	2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005 - Shanghai, China Duration: 2005 Oct 30 → 2005 Nov 2

Publication series

Name	2005 IEEE 7th Workshop on Multimedia Signal Processing

Conference

Conference	2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005
Country/Territory	China
City	Shanghai
Period	05/10/30 → 05/11/2

Keywords

Bias correction
Lossless image compression
Predictive coding

ASJC Scopus subject areas

Signal Processing

Access to Document

10.1109/MMSP.2005.248614

Cite this

Tang, H, Kamata, SI & Tsuneyoshi, K 2006, A study of bias correction methods for enhancing median edge detector prediction. in 2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005., 4014035, 2005 IEEE 7th Workshop on Multimedia Signal Processing, 2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005, Shanghai, China, 05/10/30. https://doi.org/10.1109/MMSP.2005.248614

@inproceedings{f352734dd4704cefbc6d567bbe1af1e9,

title = "A study of bias correction methods for enhancing median edge detector prediction",

abstract = "In this paper, we present three novel lossless compression approaches for gray-scale continuous tone natural image. Our methods enhance the median edge detector (MED), which is the core part of JPED-LS algorithm, by reducing the entropy of the prediction error via adaptive regression. These modified predictors improve the prediction accuracy by reducing the negative effect due to MED's oversimplified edge orientation detection. The experimental results show that our approaches achieve evidently better performance than MED with only neglectable increasing of computational complexity and without introduce extra pixels into the causal template.",

keywords = "Bias correction, Lossless image compression, Predictive coding",

author = "Haijiang Tang and Kamata, {Sei Ichiro} and Kazuyuki Tsuneyoshi",

year = "2006",

month = dec,

day = "1",

doi = "10.1109/MMSP.2005.248614",

language = "English",

isbn = "0780392892",

series = "2005 IEEE 7th Workshop on Multimedia Signal Processing",

booktitle = "2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005",

note = "2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005 ; Conference date: 30-10-2005 Through 02-11-2005",

}

TY - GEN

T1 - A study of bias correction methods for enhancing median edge detector prediction

AU - Tang, Haijiang

AU - Kamata, Sei Ichiro

AU - Tsuneyoshi, Kazuyuki

PY - 2006/12/1

Y1 - 2006/12/1

N2 - In this paper, we present three novel lossless compression approaches for gray-scale continuous tone natural image. Our methods enhance the median edge detector (MED), which is the core part of JPED-LS algorithm, by reducing the entropy of the prediction error via adaptive regression. These modified predictors improve the prediction accuracy by reducing the negative effect due to MED's oversimplified edge orientation detection. The experimental results show that our approaches achieve evidently better performance than MED with only neglectable increasing of computational complexity and without introduce extra pixels into the causal template.

AB - In this paper, we present three novel lossless compression approaches for gray-scale continuous tone natural image. Our methods enhance the median edge detector (MED), which is the core part of JPED-LS algorithm, by reducing the entropy of the prediction error via adaptive regression. These modified predictors improve the prediction accuracy by reducing the negative effect due to MED's oversimplified edge orientation detection. The experimental results show that our approaches achieve evidently better performance than MED with only neglectable increasing of computational complexity and without introduce extra pixels into the causal template.

KW - Bias correction

KW - Lossless image compression

KW - Predictive coding

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U2 - 10.1109/MMSP.2005.248614

DO - 10.1109/MMSP.2005.248614

M3 - Conference contribution

AN - SCOPUS:42749106978

SN - 0780392892

SN - 9780780392892

T3 - 2005 IEEE 7th Workshop on Multimedia Signal Processing

BT - 2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005

T2 - 2005 IEEE 7th Workshop on Multimedia Signal Processing, MMSP 2005

Y2 - 30 October 2005 through 2 November 2005

ER -

A study of bias correction methods for enhancing median edge detector prediction

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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