A Comparative Study of Histogram Equalization Techniques for Image Contrast Enhancement

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2014 by IJETT Journal
Volume-8 Number-6                          
Year of Publication : 2014
Authors : Kanchan Pandey , Asst. Prof. Sapna Singh


Kanchan Pandey , Asst. Prof. Sapna Singh."A Comparative Study of Histogram Equalization Techniques for Image Contrast Enhancement", International Journal of Engineering Trends and Technology(IJETT), V8(6),305-308 February 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group


The most significant outcome of image processing is a contrast enhancement. The most usual method of histogram equalization is used for mending contrast in digital images. Histogram equalization is so convenient and efficacious for image contrast enhancement technique. However, the conventional histogram equalization techniques usually outcome in exceeding contrast enhancement which factor the non-natural look and visible artifact of the processed image. In this paper presents a different new form of histogram for image contrast enhancement. Several methods are this establishment is the measuring used to impart the input histogram. Global Histogram Equalization GHE uses the intensity distribution of the entire image. Brightness preserving Bi-Histogram Equalization BBHE uses the mean intensity is equalized image independently. Dual Sub-Image Histogram Equalization DSIHE uses the median intensity is equalized image independently. Minimum Mean Brightness Error Bi-HE MMBEBHE uses the separation of image based on threshold level, produces the smallest Absolute Mean Brightness Error AMBE. Recursive Mean-Separate Histogram Equalization RMSHE is more different advance method of histogram equalization. Range Limited Bi-Histogram Equalization RLBHE preserves the first brightness quite well so as to separate the threshold that minimizes the intra –class variance. Survey same that everyone these strategies are more simple and useful for image contrast enhancement.


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Image Contrast Enhancement, Histogram Equalization, Brightness Preserving Enhancement, Range Limit, Histogram Partition.