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 language | English |
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Pages (from-to) | 575-592 |
Number of pages | 18 |
Journal | Applied Soft Computing Journal |
Volume | 52 |
Early online date | 20 Jan 2017 |
DOIs | |
Publication status | Published - 1 Mar 2017 |
Keywords
- Histogram equalization
- Image enhancement
- Image fusion
- Linear contrast stretching
- Particle swarm optimization algorithm
- Social spider optimization