Particle swarm optimized bi-histogram equalization for contrast enhancement and brightness preservation of images

  • Authors:
  • P. Shanmugavadivu;K. Balasubramanian;A. Muruganandam

  • Affiliations:
  • Department of Computer Science and Applications, Gandhigram Rural Institute--Deemed University, Dindigul, India;Department of Computer Applications, PSNA College of Engineering and Technology, Dindigul, India;Department of Mechanical Engineering, PSNA College of Engineering and Technology, Dindigul, India

  • Venue:
  • The Visual Computer: International Journal of Computer Graphics
  • Year:
  • 2014

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Abstract

A novel technique, Optimized Bi-Histogram Equalization (OBHE), is proposed in this paper for preserving brightness and enhancing the contrast of any input image. The central idea of this technique is to first segment the histogram of the input image into two, based on its mean and then weighting constraints are applied to each of the sub-histograms separately. Those two histograms are equalized independently and their union produces a brightness-preserved and contrast-enhanced output image. While formulating the weighting constraints, Particle Swarm Optimization (PSO) is employed to find the optimal constraints in order to maximize the degree of brightness preservation and contrast enhancement. This technique is found to have an edge over the other contemporary methods in terms of Entropy and Absolute Mean Brightness Error.