A Comparative Analysis On Image Denoising Using Different Median Filter Methods
Sandeep Kumar · International Journal for Research in Applied Science and Engineering Technology · 2017
In denoising, separation of noise from signal is a main issue, but with improved filter elimination of noise becomes easier. In this paper nonlinear median filter is used for multi resolution condition, once in full resolution and afterward with half resolution, denoising turns out to be greater. This method is a nonlinear model and is observed to be helpful in removing Impulse noise, Gaussian and Speckle noise. Further, it is recommended that utilization of a nonlinear adaptive median filter (AMF) delivers more satisfying picture with better denoising. The experimental results are based on the parameters likes Peak Signal Noise Ratio (PSNR) and Structural Similarity Matrix (SSIM). It is demonstrated that the enhanced strategy gives a high level of noise removal while protecting the edges and other data in the picture. This research is based on threshold calculation which enhances the PSNR of the framework when contrasted with combination of Discrete Wavelet Transform & Adaptive Median Filter (DWT-AMF) and other median based methods.