A social spider optimized image fusion approach for contrast enhancement and brightness preservation

Lalit Maurya, Prasant Kumar Mahapatra*, Amod Kumar

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Image enhancement means to process the image in order to obtain a visually pleasing effect on image with more perception details and less noise output. In this work, a social spider optimization based algorithm is used to produce two enhanced images, one having high sharpness or contrast with maximum entropy and the other having high peak signal-to-noise ratio (PSNR) sharp image. The two enhanced images are fused to obtain an output image which has an optimal trade-off between sharpness and noise. The proposed algorithms are applied to lathe tool images as well as to some other standard images to verify their effectiveness. The results are compared with conventional image enhancement techniques such as Histogram Equalization (HE), Linear Contrast Stretching (LCS), and Standard Particle Swarm Optimization (PSO) algorithm.

Original languageEnglish
Pages (from-to)575-592
Number of pages18
JournalApplied Soft Computing Journal
Volume52
Early online date20 Jan 2017
DOIs
Publication statusPublished - 1 Mar 2017

Keywords

  • Histogram equalization
  • Image enhancement
  • Image fusion
  • Linear contrast stretching
  • Particle swarm optimization algorithm
  • Social spider optimization

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