Novel mean-shift based histogram equalization using textured regions

Authors:
Yu-Ren Lai;Kuo-Liang Chung;Chyou-Hwa Chen;Guei-Yin Lin;Chao-Hsin Wang
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC;Graduate Institute of Automation and Control, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

Citing 14
Cited 1

Mean Shift: A Robust Approach Toward Feature Space Analysis

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fusion of classifiers for illumination robust face recognition

Expert Systems with Applications: An International Journal
Breast cancer diagnosis system based on wavelet analysis and fuzzy-neural

Expert Systems with Applications: An International Journal
An image contrast enhancement method based on genetic algorithm

Pattern Recognition Letters
The estimation of the gradient of a density function, with applications in pattern recognition

IEEE Transactions on Information Theory
Contrast enhancement using brightness preserving bi-histogram equalization

IEEE Transactions on Consumer Electronics
Image enhancement based on equal area dualistic sub-image histogram equalization method

IEEE Transactions on Consumer Electronics
A Dynamic Histogram Equalization for Image Contrast Enhancement

IEEE Transactions on Consumer Electronics
Brightness Preserving Dynamic Histogram Equalization for Image Contrast Enhancement

IEEE Transactions on Consumer Electronics
Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement

IEEE Transactions on Consumer Electronics
Image quality improvement for electrophoretic displays by combining contrast enhancement and halftoning techniques

IEEE Transactions on Consumer Electronics
Image sharpening using sub-regions histogram equalization

IEEE Transactions on Consumer Electronics
Transform Coefficient Histogram-Based Image Enhancement Algorithms Using Contrast Entropy

IEEE Transactions on Image Processing
An advanced contrast enhancement using partially overlapped sub-block histogram equalization

IEEE Transactions on Circuits and Systems for Video Technology

Automatic expert system for 3D terrain reconstruction based on stereo vision and histogram matching

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	12.06

Visualization

Abstract

This paper presents a novel mean-shift based histogram equalization method called the MSHE method. The key insight of the proposed MSHE method is that the basis of histogram equalization could be based on textured regions in an image, while impact of smoother regions should be suppressed. Using a mean-shift based approach, the sets of textured regions in an image are determined by finding regions which have a high density of edge concentration. In addition, a new cost function is presented to balance the image quality and contrast enhancement effect for search termination in the proposed algorithm. Based on three typical test images, experimental results show that our proposed MSHE method is quite competitive with the previous eleven methods, such as the HE, BBHE, DSIHE, POHE, RSWHE, DHE, BPDHE, SRHE, GHE, FHE, and THShap.