A General Histogram Modification Framework for Efficient Contrast Enhancement

Ke Gu; Guangtao Zhai; Shiqi Wang; Min Liu; Jiantao Zhou; Weisi Lin

doi:10.1109/ISCAS.2015.7169272

A General Histogram Modification Framework for Efficient Contrast Enhancement

Ke Gu, Guangtao Zhai, Shiqi Wang, Min Liu, Jiantao Zhou, Weisi Lin

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

14 Citations (Scopus)

Abstract

In this paper we propose a new general histogram modification framework for contrast enhancement. The proposed model works with a hybrid transformation technique to improve image brightness and contrast based on an optional histogram matching in terms of reassigned probability distribution and S-shaped transfer mapping. Experimental results conducted on natural, dimmed, and tone-mapped images show that the proposed technique creates enhanced images efficiently with equivalent or superior visual quality to those produced by classical and state-of-the-art enhancement approaches.

Original language	English
Title of host publication	2015 IEEE International Symposium on Circuits and Systems (ISCAS)
Publisher	IEEE
Pages	2816-2819
ISBN (Electronic)	978-1-4799-8391-9
DOIs	https://doi.org/10.1109/ISCAS.2015.7169272
Publication status	Published - May 2015
Externally published	Yes
Event	2015 IEEE International Symposium on Circuits and Systems (ISCAS 2015): Enabling Technologies for Societal Challenges - Cultural Centre of Belém, Lisbon, Portugal Duration: 24 May 2015 → 27 May 2015 http://www.iscas2015.org/

Conference

Conference	2015 IEEE International Symposium on Circuits and Systems (ISCAS 2015)
Place	Portugal
City	Lisbon
Period	24/05/15 → 27/05/15
Internet address	http://www.iscas2015.org/

Research Keywords

Contrast enhancement
histogram matching
histogram modification (HM)
reassigned probability distribution
S-shaped transfer mapping

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10.1109/ISCAS.2015.7169272

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@inproceedings{fe61f5f0f7794d89a61d703949cdcf65,

title = "A General Histogram Modification Framework for Efficient Contrast Enhancement",

abstract = "In this paper we propose a new general histogram modification framework for contrast enhancement. The proposed model works with a hybrid transformation technique to improve image brightness and contrast based on an optional histogram matching in terms of reassigned probability distribution and S-shaped transfer mapping. Experimental results conducted on natural, dimmed, and tone-mapped images show that the proposed technique creates enhanced images efficiently with equivalent or superior visual quality to those produced by classical and state-of-the-art enhancement approaches.",

keywords = "Contrast enhancement, histogram matching, histogram modification (HM), reassigned probability distribution, S-shaped transfer mapping",

author = "Ke Gu and Guangtao Zhai and Shiqi Wang and Min Liu and Jiantao Zhou and Weisi Lin",

year = "2015",

month = may,

doi = "10.1109/ISCAS.2015.7169272",

language = "English",

pages = "2816--2819",

booktitle = "2015 IEEE International Symposium on Circuits and Systems (ISCAS)",

publisher = "IEEE",

address = "United States",

note = "2015 IEEE International Symposium on Circuits and Systems (ISCAS 2015) : Enabling Technologies for Societal Challenges ; Conference date: 24-05-2015 Through 27-05-2015",

url = "http://www.iscas2015.org/",

}

Gu, K, Zhai, G, Wang, S, Liu, M, Zhou, J & Lin, W 2015, A General Histogram Modification Framework for Efficient Contrast Enhancement. in 2015 IEEE International Symposium on Circuits and Systems (ISCAS)., 7169272, IEEE, pp. 2816-2819, 2015 IEEE International Symposium on Circuits and Systems (ISCAS 2015), Lisbon, Portugal, 24/05/15. https://doi.org/10.1109/ISCAS.2015.7169272

A General Histogram Modification Framework for Efficient Contrast Enhancement. / Gu, Ke; Zhai, Guangtao; Wang, Shiqi et al.
2015 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2015. p. 2816-2819 7169272.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - A General Histogram Modification Framework for Efficient Contrast Enhancement

AU - Gu, Ke

AU - Zhai, Guangtao

AU - Wang, Shiqi

AU - Liu, Min

AU - Zhou, Jiantao

AU - Lin, Weisi

PY - 2015/5

Y1 - 2015/5

N2 - In this paper we propose a new general histogram modification framework for contrast enhancement. The proposed model works with a hybrid transformation technique to improve image brightness and contrast based on an optional histogram matching in terms of reassigned probability distribution and S-shaped transfer mapping. Experimental results conducted on natural, dimmed, and tone-mapped images show that the proposed technique creates enhanced images efficiently with equivalent or superior visual quality to those produced by classical and state-of-the-art enhancement approaches.

AB - In this paper we propose a new general histogram modification framework for contrast enhancement. The proposed model works with a hybrid transformation technique to improve image brightness and contrast based on an optional histogram matching in terms of reassigned probability distribution and S-shaped transfer mapping. Experimental results conducted on natural, dimmed, and tone-mapped images show that the proposed technique creates enhanced images efficiently with equivalent or superior visual quality to those produced by classical and state-of-the-art enhancement approaches.

KW - Contrast enhancement

KW - histogram matching

KW - histogram modification (HM)

KW - reassigned probability distribution

KW - S-shaped transfer mapping

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U2 - 10.1109/ISCAS.2015.7169272

DO - 10.1109/ISCAS.2015.7169272

M3 - RGC 32 - Refereed conference paper (with host publication)

SP - 2816

EP - 2819

BT - 2015 IEEE International Symposium on Circuits and Systems (ISCAS)

PB - IEEE

T2 - 2015 IEEE International Symposium on Circuits and Systems (ISCAS 2015)

Y2 - 24 May 2015 through 27 May 2015

ER -

A General Histogram Modification Framework for Efficient Contrast Enhancement

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Research Keywords

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