Cognition model based adaptive multilevel filter for removal of impulse noise

Image denoising is an important image processing task, both as a process itself, and as a component in other processes. The main properties of a good image denoising model are that it will remove noise while preserving edges. This paper presents a novel adaptive multilevel filter based on the cloud model (CM) to remove impulse noise; CM is an uncertain cognitive model called the CM filter. First, an uncertainty-based detector identifies the pixels corrupted by impulse noise. Then, a weighted multilevel arithmetic mean filter is applied to remove the noise candidates. Compared with the traditional filters, the CM filter makes a great improvement in image denoising.