Novel method to assess motion blur kernel parameters and comparative study of restoration techniques using different image layouts

In general, recorded image can perpetually characterized a degraded version of the original image caused by inadequacy in the imaging and capturing process. There exists several kinds of degradations that need to be considered to restore degraded images. Such kinds of degradations are blur, noise, illumination and color imperfections. Among those, two major categories of degradations namely, motion blur and noise are considered in this study. For restoring degraded image, it is important to know the degradation function, commonly point spread function (PSF) of blurred image. This study focuses an approach to assess PSF parameters from blurred and noisy images. Furthermore, this study presents comparative analysis of different non-blind image restoration techniques based on Wiener and Lucy-Richardson algorithm for different types of image layouts. The experimental result illustrates blur images without noise and with noise are successfully restored.