CONTRAST ENHANCEMENT USING TEXTURE HISTOGRAM AND FUZZY ENTROPY

Yanhui Guo (), H. D. Cheng (), Jianhua Huang (), Wei Zhao () and Xianglong Tang ()
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Yanhui Guo: School of Computer Science and Technology, P.O. Box 352, Harbin Institute of Technology, Harbin,150001, China
H. D. Cheng: Department of Computer Science, Utah State University, Logan, UT 84322-4205, USA
Jianhua Huang: School of Computer Science and Technology, Harbin Institute of Technology, P.O. Box 352, Harbin, 150001, China
Wei Zhao: School of Computer Science and Technology, Harbin Institute of Technology, P.O. Box 352, Harbin, 150001, China
Xianglong Tang: School of Computer Science and Technology, Harbin Institute of Technology, P.O. Box 352, Harbin, 150001, China

New Mathematics and Natural Computation (NMNC), 2007, vol. 03, issue 03, 349-365

Abstract: Image enhancement is used to correct contrast deficiencies and to improve the quality of an image. It is essential and critical to extracting features and segmenting images. This paper presents a novel contrast enhancement algorithm based on newly defined texture histogram and fuzzy entropy with the ability to preserve edges and details, while avoiding noise amplification and over-enhancement. To demonstrate the performance, the proposed algorithm is tested on a variety of images and compared with other enhancement algorithms. Experimental results proved that the proposed method has better performance in enhancing images without over-enhancement and under-enhancement.

Keywords: Contrast enhancement; fuzzy logic; texture analysis; maximum entropy principle (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1142/S1793005707000835

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