PSO Algorithm based Adaptive Median Filter for Noise Removal in Image Processing Application

A adaptive Switching median filter for salt and pepper noise removal based on genetic algorithm is presented. Proposed filter consist of two stages, a noise detector stage and a noise filtering stage. Particle swarm optimization seems to be effective for single objective problem. Noise Dictation stage works on it. In contrast to the standard median filter, the proposed algorithm generates the noise map of corrupted Image. Noise map gives information about the corrupted and non-corrupted pixels of Image. In filtering, filter calculates the median of uncorrupted neighbouring pixels and replaces the corrupted pixels. Extensive simulations are performed to validate the proposed filter. Simulated results show refinement both in Peak signal to noise ratio (PSNR) and Image Quality Index value (IQI). Experimental results shown that proposed method is more effective than existing methods.

@article{Verma2016,
  title     = {PSO Algorithm based Adaptive Median Filter for Noise Removal in Image Processing Application},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {7},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Ruby Verma and Rajesh Mehra},
  doi       = {10.14569/IJACSA.2016.070713},
  url       = {https://doi.org/10.14569/IJACSA.2016.070713}
}