Matlab Program for Sharpening Image due to Lenses Blurring Effect Simulation with Lucy Richardson Deconvolution

Abstract

This research was conducted to simulate digital image sharpening using the Lusi Richardson deconvolution method. Sharpening was then performed by Lusi richardson deconvolution of the pint spread function of the lens effect. This point spread function is modeled mathematically with a mathematical function approach. The results of the convolution between the Digital Image from a photo of an object are then convolved with the point spread function so as to produce a blurry image. The blurry image is then re-sharpened by deconvolution using the Lucy Richardson convolution method. The results of this deconvolution are then compared with the image of an object photo of reference and then the difference is calculated. The slight difference between the deconvolution result image and the original object photo image indicates that the program is running well. Peak Signal to Noise Ratio (PSNR) Is used to determine image sharpening recovery. The optimum sharpening recovery of deconvolution iteration is obtained in the maximum PSNR value