Abstract— One of the important implementations in image-processing field is the image restoration. Image restoration deals with the recovery of an original image from a degraded image using a mathematical model of degradation and restoration for image. Image restoration is becoming more and more important in the image-processing field, and it is very important in many applications like medical, satellite and photography. In spite of the various existing solutions available to image restoration, there is always a need for more efficient methods. In this paper, several restoration and deconvolution techniques, experimented and tested, we used both blind and non-blind techniques. Then we propose a combination between blind and non-blind techniques in order to improve the quality of the restored image. Several types of noise are added to the image after it has been blurred. We have tested the behavior of the different filters and techniques in removing each type of noise. The evaluation of the filters behaviors and the conclusion are done based on various metrics like PSNR, MSE, RMSE and IEF.
Keywords— Image processing, Image restoration, blind and non-blind techniques, Noise, Metrics.
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