Usually we have a large number of devices by which we can take pictures, from a digital camera to a cell phone. Problem is that usually we take the picture we don’t see some errors that can be present in the image until we observe it in a computer or printed image. Now the real problem arises because it is almost impossible to recapture the same moment in a new photo. Hence to find a solution for this problem comes the need to implement a method to correct some of the defects that appear. In this paper we compare different methods, problems and their proposed solutions algorithms to patch an original image, using different texture image techniques. Traditional match matching algorithms treat each pixel/patch as an independent sample and build a hierarchical data structure, such as the kd-tree, to accelerate nearest patch finding. However, most of these approaches can only find approxi-mate nearest patch and do not explore the sequential overlap between patches. Hence, they are neither accurate in quality nor optimal in speed.