Differential histogram equalization based image simplification

Yi Ta Wu; Frank Y. Shih; Yih Tyng Wu

doi:10.1109/EIT.2006.252185

Differential histogram equalization based image simplification

Yi Ta Wu, Frank Y. Shih, Yih Tyng Wu

Computer Science

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

4 Scopus citations

Abstract

Image simplification is an important pre-processing task in object segmentation and recognition. The histogram-based approach is the simplest way of image simplification. However, it is difficult to find a general rule of obtaining the proper threshold for all different cases. Recently, the research on image simplification using morphology seems to achieve a better performance. Nevertheless, the quality of simplification results relies on the selection of maskers obtained from complicated morphological operations. In this paper, we present a new perspective view based on differential histogram equalization (DHE) in image simplification. It is developed to not only generate better quality results, but possess lower computational complexity.

Original language	English (US)
Title of host publication	2006 IEEE International Conference on Electro Information Technology
Pages	344-349
Number of pages	6
DOIs	https://doi.org/10.1109/EIT.2006.252185
State	Published - 2006
Event	2006 IEEE International Conference on Electro Information Technology - East Lansing, MI, United States Duration: May 7 2006 → May 10 2006

Publication series

Name	2006 IEEE International Conference on Electro Information Technology

Other

Other	2006 IEEE International Conference on Electro Information Technology
Country/Territory	United States
City	East Lansing, MI
Period	5/7/06 → 5/10/06

All Science Journal Classification (ASJC) codes

General Computer Science
Electrical and Electronic Engineering
Control and Systems Engineering
Biomedical Engineering
Automotive Engineering

Keywords

Histogram equalization
Image representation
Image simplification
Segmentation

Access to Document

10.1109/EIT.2006.252185

Cite this

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title = "Differential histogram equalization based image simplification",

abstract = "Image simplification is an important pre-processing task in object segmentation and recognition. The histogram-based approach is the simplest way of image simplification. However, it is difficult to find a general rule of obtaining the proper threshold for all different cases. Recently, the research on image simplification using morphology seems to achieve a better performance. Nevertheless, the quality of simplification results relies on the selection of maskers obtained from complicated morphological operations. In this paper, we present a new perspective view based on differential histogram equalization (DHE) in image simplification. It is developed to not only generate better quality results, but possess lower computational complexity.",

keywords = "Histogram equalization, Image representation, Image simplification, Segmentation",

author = "Wu, {Yi Ta} and Shih, {Frank Y.} and Wu, {Yih Tyng}",

year = "2006",

doi = "10.1109/EIT.2006.252185",

language = "English (US)",

isbn = "078039593X",

series = "2006 IEEE International Conference on Electro Information Technology",

pages = "344--349",

booktitle = "2006 IEEE International Conference on Electro Information Technology",

note = "2006 IEEE International Conference on Electro Information Technology ; Conference date: 07-05-2006 Through 10-05-2006",

}

Wu, YT, Shih, FY & Wu, YT 2006, Differential histogram equalization based image simplification. in 2006 IEEE International Conference on Electro Information Technology., 4017722, 2006 IEEE International Conference on Electro Information Technology, pp. 344-349, 2006 IEEE International Conference on Electro Information Technology, East Lansing, MI, United States, 5/7/06. https://doi.org/10.1109/EIT.2006.252185

TY - GEN

T1 - Differential histogram equalization based image simplification

AU - Wu, Yi Ta

AU - Shih, Frank Y.

AU - Wu, Yih Tyng

PY - 2006

Y1 - 2006

N2 - Image simplification is an important pre-processing task in object segmentation and recognition. The histogram-based approach is the simplest way of image simplification. However, it is difficult to find a general rule of obtaining the proper threshold for all different cases. Recently, the research on image simplification using morphology seems to achieve a better performance. Nevertheless, the quality of simplification results relies on the selection of maskers obtained from complicated morphological operations. In this paper, we present a new perspective view based on differential histogram equalization (DHE) in image simplification. It is developed to not only generate better quality results, but possess lower computational complexity.

AB - Image simplification is an important pre-processing task in object segmentation and recognition. The histogram-based approach is the simplest way of image simplification. However, it is difficult to find a general rule of obtaining the proper threshold for all different cases. Recently, the research on image simplification using morphology seems to achieve a better performance. Nevertheless, the quality of simplification results relies on the selection of maskers obtained from complicated morphological operations. In this paper, we present a new perspective view based on differential histogram equalization (DHE) in image simplification. It is developed to not only generate better quality results, but possess lower computational complexity.

KW - Histogram equalization

KW - Image representation

KW - Image simplification

KW - Segmentation

UR - http://www.scopus.com/inward/record.url?scp=34250880675&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34250880675&partnerID=8YFLogxK

U2 - 10.1109/EIT.2006.252185

DO - 10.1109/EIT.2006.252185

M3 - Conference contribution

AN - SCOPUS:34250880675

SN - 078039593X

SN - 9780780395930

T3 - 2006 IEEE International Conference on Electro Information Technology

SP - 344

EP - 349

BT - 2006 IEEE International Conference on Electro Information Technology

T2 - 2006 IEEE International Conference on Electro Information Technology

Y2 - 7 May 2006 through 10 May 2006

ER -

Differential histogram equalization based image simplification

Abstract

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All Science Journal Classification (ASJC) codes

Keywords

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