Development of Algorithm for Dynamic Hybrid Mean/Median Filter using Adaptive Window Selection Approach to Eliminate Salt & Pepper Noise


  • Neha Patil VTU
  • Dr. V.R Udupi VTU





Adaptive, Filter, Multimedia Data, Noisy Data, Salt Pepper Noise.


The research work aimed to develop a new Dynamic Hybrid Mean/Median Filter (DHMMF) algorithm to eliminate salt & pepper noise. The proposed DHMMF algorithm decides window size dynamically during runtime, also adaptively adjusts window size based on the non-noisy pixels present in a local window. Window size is limited to 9 X 9. This reduces blurring and computational complexity. Filter is designed with two stages, noise detection succeeded by filtering strategy. During the noise detection stage, if pixel intensity value is in-between 1 to 254, it is classified as a non-noisy pixel and left unchanged. Pixel having 0 or 255 intensity value is classified as a noisy pixel. During the filtering stage, a noisy pixel is replaced with mean, median or trimmed values within a local window depending on various algorithmic conditions. Performance of DHMMF algorithm is compared with various existing methods. Performance is tested for low, medium and high density noise. Simulation results demonstrate that image quality is retained by preserving fine details and edges which results in better visual quality. Quantitative and qualitative analysis is carried out using PSNR and SSIM respectively.




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