Quraishi, Md. Iqbal; De, Mallika; Das, Goutam
April 2013
Asian Journal of Computer Science & Information Technology;Apr2013, Vol. 3 Issue 4, p69
Academic Journal
Particle Swarm Optimization (PSO) algorithm represents a nature inspired approach for optimization problems. In this paper image enhancement is considered as an optimization problem. Enhancement of images is mainly done by maximizing the information content of the actual image. In the present work a parameterized fitness function is used, which uses local and global information of the images. An objective criterion for measuring image enhancement is used which considers neighborhood and fitness data of the images. Results are compared and analyzed with other enhancement techniques like Histogram Equalization (HE), Linear Contrast Stretching (LCS) and Genetic Algorithm (GA) based image Enhancements. Quality parameters such as Root Mean Square error, Peak Signal to Noise Ratio has been calculated along with Normalized Cross Correlation, Average Difference, Structural content, Maximum Difference, Normalized Absolute Error to verify the effectiveness of Particle Swarm Optimizations an image enhancement technique.


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