Performance evaluation of image restoration methods for comparative analysis with and without noise

As the picture worth thousands words, it is necessary to restore the degraded images degraded because of blur, motion or noise in applications like satellite imaging, medical imaging, military and survivalance applications. Restorations techniques are either nonblind methods where the point spread function (PSF) is available or blind deconvolution. This paper presents the implementation and comparison of Weiner filter, Constrained Lease Square, Lucy Richerdson and Blind deconvolution methods in the presence of different artifacts. Performance measures like Peak signal to noise ratio (PSNR), Mean square error (MSE) and Correlation index (CI) are used to quantify the performance of the restoration filters. Results and analysis shows that CLS filter is comparatively better in restoring the degraded image.