Contrast enhancement by automatic and parameter-free piecewise linear transformation for color images

Conventional contrast enhancement methods have four shortcomings. First, most of them need transformation functions and parameters which are specified manually. Second, most of them are application-oriented methods. Third, most of them are performed on gray level images. Fourth, the histogram equali...

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Bibliographic Details
Published inIEEE transactions on consumer electronics Vol. 54; no. 2; pp. 213 - 219
Main Authors Tsai, Chun-Ming, Yeh, Zong-Mu
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2008
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive equalizers
Algorithms
Back
Color
Equalization
Histograms
Image analysis
Image contrast
Image processing
Lighting
Methods
Mobile communication systems
Piecewise linear techniques
Real time systems
Studies
Transformations
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Summary:Conventional contrast enhancement methods have four shortcomings. First, most of them need transformation functions and parameters which are specified manually. Second, most of them are application-oriented methods. Third, most of them are performed on gray level images. Fourth, the histogram equalization (HE) based enhancement methods use non-linear transform function. Thus, this paper proposes an automatic and parameter-free contrast enhancement algorithm for color images. This method includes following steps: First, RGB color space is transformed to HSV color space. Second, image content analysis is used to analyze the image illumination distribution. Third, the original image is enhanced by piecewise linear based enhancement method. Finally, the enhancement image is transformed back to RGB color space. This novel enhancement is automatic and parameter-free. Our experiments included various color images with low and high contrast. Experiment results show that the performance of the proposed method is better than histogram equalization (HE) and its six variations in non-over enhancement and natural clearly revealed. Moreover, the proposed algorithm can be run on an embedded environment (such as mobile device, digital camera, or other consumer products) and processed in real-time system due to its simplicity and efficiently.
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ISSN:0098-3063
1558-4127
DOI:10.1109/TCE.2008.4560077