the Restoration of degraded images by using the Straubel pupil function filter mask

Restoration of degraded images

Abstract

Restoration is a process by which an image suffering from degradation can be recovered to its original form, Image restoration is an important issue in high-level image processing which deals with recovering an original and sharp image using a degradation and restoration model, removing blur and noise from image is complicated problem to solve, to get an enough efficient method to remove the noise from the images is a greater challenge for the researchers, Sometimes, the captured image gets blurry and there is noise from the environment, Degradation may occur due to noise, motion blur, Gaussian blur, camera mismatch, non-uniform illumination, and low-contrast image. Depending on the pupil function technique for images of point objects, the proposed method integrates the design of a new amplitude filter mask to improve image quality. our filter was intended to restore blurry and noisy images using MATLAB software, The performance of this algorithm has been compared with CLAHE and HE algorithms. the statistical image quality measurement is based on the signal-to-noise ratio (PSNR), Error Relative Global Dimensionally de Synthase (ERGAS), image entropy, Structural Similarity Index (SSIM), Root Mean Square (RMSE), and Enhancement Measure Estimation (EME). The experiment results show when all parameters are compared that our filter implementation technique for image restoration recovers the damaged image.