Abstract
Computer vision systems largely depend on the quality of output of the image processing modules to perform their operations for a desired accurate result. The process of image acquisition and transmission usually results in image degradation. This endangers the efficiency of computer vision systems. This paper presents the causes of image degradation and the restoration techniques to enhance the output of computer vision systems. At different filter kernel sizes, median filters have better performance in image restoration as shown in the SNR, PSNR, and MSE results obtained. Averaging filters result in a blurring effect on the image. Wiener filters perform better for speckle and Gaussian noise. For impulse (salt and pepper) noise, median filters have the best performance.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
