IEICE TRANSACTIONS on Information
Image Contrast Enhancement Using Adaptive Slope
Summary :
In this paper, we propose an algorithm for contrast enhancement based on Adaptive Histogram Equalization (AHE) to improve image quality. Most histogram-based contrast enhancement methods have problems with excessive or low image contrast enhancement. This results in unnatural output images and the loss of visual information. The proposed method manipulates the slope of the input of the Probability Density Function (PDF) histogram. We also propose a pixel redistribution method using convolution to compensate for excess pixels after the slope modification procedure. Our method adaptively enhances the contrast of the input image and shows good simulation results compared with conventional methods.
- Publication
- IEICE TRANSACTIONS on Information Vol.E97-D No.5 pp.1382-1385
- Publication Date
- 2014/05/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E97.D.1382
- Type of Manuscript
- LETTER
- Category
- Image Processing and Video Processing
Authors
Hwa-Soo WOO
Hanyang University
Jong-Wha CHONG
Hanyang University
Keyword
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Hwa-Soo WOO, Jong-Wha CHONG, "Image Contrast Enhancement Using Adaptive Slope" in IEICE TRANSACTIONS on Information,
vol. E97-D, no. 5, pp. 1382-1385, May 2014, doi: 10.1587/transinf.E97.D.1382.
Abstract: In this paper, we propose an algorithm for contrast enhancement based on Adaptive Histogram Equalization (AHE) to improve image quality. Most histogram-based contrast enhancement methods have problems with excessive or low image contrast enhancement. This results in unnatural output images and the loss of visual information. The proposed method manipulates the slope of the input of the Probability Density Function (PDF) histogram. We also propose a pixel redistribution method using convolution to compensate for excess pixels after the slope modification procedure. Our method adaptively enhances the contrast of the input image and shows good simulation results compared with conventional methods.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E97.D.1382/_p
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@ARTICLE{e97-d_5_1382,
author={Hwa-Soo WOO, Jong-Wha CHONG, },
journal={IEICE TRANSACTIONS on Information},
title={Image Contrast Enhancement Using Adaptive Slope},
year={2014},
volume={E97-D},
number={5},
pages={1382-1385},
abstract={In this paper, we propose an algorithm for contrast enhancement based on Adaptive Histogram Equalization (AHE) to improve image quality. Most histogram-based contrast enhancement methods have problems with excessive or low image contrast enhancement. This results in unnatural output images and the loss of visual information. The proposed method manipulates the slope of the input of the Probability Density Function (PDF) histogram. We also propose a pixel redistribution method using convolution to compensate for excess pixels after the slope modification procedure. Our method adaptively enhances the contrast of the input image and shows good simulation results compared with conventional methods.},
keywords={},
doi={10.1587/transinf.E97.D.1382},
ISSN={1745-1361},
month={May},}
Copy
TY - JOUR
TI - Image Contrast Enhancement Using Adaptive Slope
T2 - IEICE TRANSACTIONS on Information
SP - 1382
EP - 1385
AU - Hwa-Soo WOO
AU - Jong-Wha CHONG
PY - 2014
DO - 10.1587/transinf.E97.D.1382
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E97-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2014
AB - In this paper, we propose an algorithm for contrast enhancement based on Adaptive Histogram Equalization (AHE) to improve image quality. Most histogram-based contrast enhancement methods have problems with excessive or low image contrast enhancement. This results in unnatural output images and the loss of visual information. The proposed method manipulates the slope of the input of the Probability Density Function (PDF) histogram. We also propose a pixel redistribution method using convolution to compensate for excess pixels after the slope modification procedure. Our method adaptively enhances the contrast of the input image and shows good simulation results compared with conventional methods.
ER -
English
