scholarly journals Modified Histogram Equalization for Image Contrast Enhancement Using Particle Swarm Optimization

2011 ◽  
Vol 1 (5) ◽  
pp. 13-27 ◽  
Author(s):  
P Shanmugavadivu
Keyword(s):  
Particle Swarm Optimization ◽  
Contrast Enhancement ◽  
Particle Swarm ◽  
Histogram Equalization ◽  
Image Contrast ◽  
Swarm Optimization ◽  
Image Contrast Enhancement

scholarly journals Implementation of Modified Particle Swarm Optimization Algorithm for Image Contrast Enhancement

2020 ◽  
Vol 9 (4) ◽  
pp. 1030-1036
Keyword(s):  
Image Processing ◽  
Particle Swarm Optimization ◽  
Contrast Enhancement ◽  
Particle Swarm ◽  
Histogram Equalization ◽  
Image Contrast ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Image Contrast Enhancement ◽  
Overall Evaluation

Image contrast enhancement is mostly preferred approach for Medical Image Processing field. In this work, a new Histogram Specification (HS) based image contrast enhancement scheme is described. The optimal values of the weighing constraints are progressed through the standard of Modified Particle Swarm Optimization (MPSO) with respect to the histogram of the input processed images. The proposed scheme improves the contrast of the input processed image superior than its existing histogram equalization methods. Henceforth, this method can efficiently be utilized in the fields including image processing, electronics etc. The overall evaluation of the HS scheme can be computed by means of Discrete Entropy (DE) and Contrast Improvement Index (CII).

Infrared Image Contrast Enhancement Based on Modified Particle Swarm Optimization

2013 ◽  
Vol 760-762 ◽  
pp. 1389-1393
Author(s):  
Ren Tao Zhao ◽  
You Yu Wang ◽  
Hua De Li ◽  
Jun Tie
Keyword(s):  
Particle Swarm Optimization ◽  
Contrast Enhancement ◽  
Particle Swarm ◽  
Infrared Image ◽  
Optimal Solution ◽  
Image Contrast ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Image Contrast Enhancement ◽  
Modified Pso

Adaptive infrared image contrast enhancement is presented based on modified particle swarm optimization (PSO) and incomplete Beta Function. On the basis of traditional PSO, modified PSO integrates into the theory of Multi-Particle Swarm and evolution theory algorithm. By using separate search space optimal solution of multiple particles, the global search ability is improved. And in the iteration procedures, timely adjustment of acceleration coefficients is convenient for PSO to find the global optimal solution in the later iteration. Through infrared image simulation, experimental results show that the modified PSO is better than the standard PSO in computing speed and convergence.

scholarly journals Local Contrast Enhancement Utilizing Bidirectional Switching Equalization of Separated and Clipped Subhistograms

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Haidi Ibrahim ◽  
Seng Chun Hoo
Keyword(s):  
Contrast Enhancement ◽  
Histogram Equalization ◽  
Processing Technique ◽  
Image Contrast ◽  
Local Contrast ◽  
Image Contrast Enhancement ◽  
Enhancement Method ◽  
Equalization Technique ◽  
Histogram Bins ◽  
Almost All

Digital image contrast enhancement methods that are based on histogram equalization technique are still useful for the use in consumer electronic products due to their simple implementation. However, almost all the suggested enhancement methods are using global processing technique, which does not emphasize local contents. Therefore, this paper proposes a new local image contrast enhancement method, based on histogram equalization technique, which not only enhances the contrast, but also increases the sharpness of the image. Besides, this method is also able to preserve the mean brightness of the image. In order to limit the noise amplification, this newly proposed method utilizes local mean-separation, and clipped histogram bins methodologies. Based on nine test color images and the benchmark with other three histogram equalization based methods, the proposed technique shows the best overall performance.

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