Image Restoration is defined as method to restore the degraded or corrupted images. There are many restoration methods available and implemented to recover the corrupted images. Filling-in of missing and corrupted information is very important technique in image restoration. When images are transmitted, if some of information is lost then reconstruction of the lost data using correlation between the lost block and its neighbors has been used. The basic idea is fill-in the missing block with

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... rmation propagating from the surrounding pixels. This paper presented novel and efficient algorithm that combines the advantages of two filling-in techniques. In this paper, "Hybrid Filling-in technique for image restoration" is presented in which two filling-in techniques are used to restore the damaged image. In the hybrid technique first Probabilistic Recovery Filling-in technique is implemented to find out the distortion in the pixels. In this technique corrupted and missing pixels are founded according to low density of pixels and restored by using information from the surrounding pixels. After this approach the proposed filling-in technique is implemented to restore the noisy and distorted image in which GLCM is used to scan the properties of image. This research will provide better quality of results as compare to previous techniques. Then the results of Probabilistic Recovery and Hybrid Filling-in techniques are compared.