الفهرس 
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Abstract
Film or video could be described as a series of images or picture, the random pattern superimposed on the picture, visible as a random flicker of ”dots” or ”snow”, is the result of electronic noise and radiated electromagnetic noise. Corruption or noise is a common problem in any field which makes use of images as a film frame or video frame which is one of the many still images which compose the complete moving picture .If the archive film or video material is to be broadcast, it is desirable to remove unwanted noise/corruption from the original material, prior to broadcast. The effect of noise is most commonly seen in the old videos; the loss and distortion of the feature at films silent-era constitute an alarming in cultural recording for most nations. So the noise removal is an important task in video restoration where the ”original” video is discernible. In image processing, noise reduction and restoration of the image is expected to improve the qualitative inspection of images and so the performance criteria of quantitative image analysis techniques. The kinds of noise removal algorithms depends on the type of noise present in the image, several types of linear and nonlinear filtering techniques have been proposed where each of them has their own limitation and advantages. Most of the techniques that used for image restoration are oriented towards modeling the degradations- usually blur and noise- and applying various filters to obtain an approximation of the original scene. This thesis presents the performance analysis of different nonlinear filtering schemes and benefit in a choice of applicable denoising algorithm as: untrimmed decision based median filter (UDBMF), decision based median filter (DBMF), weighted median filter (WMF), and standard median filter (SMF). The work investigates the goal of restoration of digital images and videos in four steps. Step one provides an overview of effective algorithms in image restoration. While step two represents a suggested new cascaded filtering technique to improve the denoising process in digital images. In step three; the work is contemplated to introduce reviews of some algorithms that can be used to restore the corrupted video that presented in Audio Video Interlaced (AVI) container format. Finally; in step four, an efficient approach for video denoising is implemented which deals with Gaussian, Salt-pepper, and Speckle noise removing.A comparable analysis among all filters is done at different levels of noise based on the visual impression; besides, some parameters are calculated to validate the performance of the various filters that used in restoration, these parameters as mean square error (MSE), mean absolute error (MAE), image enhancement factor (IEF), peak signal to noise ratio (PSNR), and correlation ratio (CORR).The results have shown that the suggested methodology has the potential to be applied in image and video restoration with achievable good performance. Besides, the necessary details in video were preserved.