A two-dimensional smoothing template for digital image preprocessing

Abstract

The theories of least-squares estimation and nonlinear function fitting are applied to solve the problem of data smoothing in image processing. Based on the derived algorithm, a novel spatial-domain template with variable mask size is obtained. It can preserve the important information in digital images as it smooths. Experimental results and detailed case studies have shown that the derived template has advantages over the commonly adopted filtering masks. The quality of the resulting images is very good, even under strongly noise-corrupted conditions.<>