Image processing plays a vital role in the computer vision because most of the scenarios require object extraction & recognition. But there lies a self-concatenated issue with it because such an algorithm is also supposed to simultaneously solves the problem of image restoration and transmission. In order to achieve this objective we furthered the effective ABLATA algorithm for the same Once the image is denoised and features are extracted then it can be resized to the half of the actual image, compressing it in a mathematical equation that shall help it restore with the half of the data and thus can readily be restored with the half of the actual imagery data to reproduce it, while maintaining the high image quality. The advantage of such a process is the low storage cost and image transmission requires less time than that required by the original one.