Shape preserving local contrast enhancement

Vicent Caselles; Jose Luis Lisani; Jean Michel Morel; Guillermo Sapiro

doi:10.1109/icip.1997.647769

Shape preserving local contrast enhancement

Vicent Caselles
, Jose Luis Lisani
, Jean Michel Morel
, Guillermo Sapiro

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

26 Citations (Scopus)

Abstract

A novel approach for shape preserving contrast enhancement is presented in this paper. Contrast enhancement is achieved by means of a local histogram equalization algorithm which preserves the level-sets of the image. This basic property is violated by common local schemes, thereby introducing spurious objects and modifying the image information. The scheme is based on equalizing the histogram in all the connected components of the image, which are defined based on the image grey-values and spatial relations between its pixels. Following mathematical morphology, these constitute the basic objects in the scene. We give examples for both grey-valued and color images.

Original language	English
Title of host publication	IEEE International Conference on Image Processing
Publisher	IEEE Computer Society
Pages	314-317
Volume	1
DOIs	https://doi.org/10.1109/icip.1997.647769
Publication status	Published - 1997
Externally published	Yes
Event	Proceedings of the 1997 International Conference on Image Processing. Part 2 (of 3) - Santa Barbara, CA, USA Duration: 26 Oct 1997 → 29 Oct 1997

Conference

Conference	Proceedings of the 1997 International Conference on Image Processing. Part 2 (of 3)
City	Santa Barbara, CA, USA
Period	26/10/97 → 29/10/97

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This work was partially supported by DGICYT-PB94-1174, and by the Math, Computer, and Information Sciences Division at ONR. Part of this work was performed while GS was at HP Labs, California.

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10.1109/icip.1997.647769

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title = "Shape preserving local contrast enhancement",

abstract = "A novel approach for shape preserving contrast enhancement is presented in this paper. Contrast enhancement is achieved by means of a local histogram equalization algorithm which preserves the level-sets of the image. This basic property is violated by common local schemes, thereby introducing spurious objects and modifying the image information. The scheme is based on equalizing the histogram in all the connected components of the image, which are defined based on the image grey-values and spatial relations between its pixels. Following mathematical morphology, these constitute the basic objects in the scene. We give examples for both grey-valued and color images.",

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AU - Lisani, Jose Luis

AU - Morel, Jean Michel

AU - Sapiro, Guillermo

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N2 - A novel approach for shape preserving contrast enhancement is presented in this paper. Contrast enhancement is achieved by means of a local histogram equalization algorithm which preserves the level-sets of the image. This basic property is violated by common local schemes, thereby introducing spurious objects and modifying the image information. The scheme is based on equalizing the histogram in all the connected components of the image, which are defined based on the image grey-values and spatial relations between its pixels. Following mathematical morphology, these constitute the basic objects in the scene. We give examples for both grey-valued and color images.

AB - A novel approach for shape preserving contrast enhancement is presented in this paper. Contrast enhancement is achieved by means of a local histogram equalization algorithm which preserves the level-sets of the image. This basic property is violated by common local schemes, thereby introducing spurious objects and modifying the image information. The scheme is based on equalizing the histogram in all the connected components of the image, which are defined based on the image grey-values and spatial relations between its pixels. Following mathematical morphology, these constitute the basic objects in the scene. We give examples for both grey-valued and color images.

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DO - 10.1109/icip.1997.647769

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

VL - 1

SP - 314

EP - 317

BT - IEEE International Conference on Image Processing

PB - IEEE Computer Society

T2 - Proceedings of the 1997 International Conference on Image Processing. Part 2 (of 3)

Y2 - 26 October 1997 through 29 October 1997

ER -

Shape preserving local contrast enhancement

Abstract

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