Image Denoising with 2D FIR Filter by using Binary Cat Swarm Optimization

A very vast portion of digital image processing is concerned with image de-noising. This includes research in algorithm and routine goal oriented image Processing. Image restoration is the removal or reduction of degraded images that are Incurred while the image is being obtained. Degradation comes from blurring as Well as noise due to various sources. Blurring is a form of bandwidth reduction in the image caused by the imperfect image formation process like relative motion between the camera & the object or by an optical system which is out of the focus. When aerial photographs are taken for remote sensing purposes, atmospheric turbulence introduces blurs, optical system aberration and relative motion between camera and the ground. With these blurring effects, the recorded image can also be corrupted by noises. A noise can be introduced in the transmission medium due to a noisy channel, errors during the measurement process and during quantization of the data for digital storage. Each element in the imaging chain such as film, lenses, digitizer, etc. contribute to the degradation. In this paper, two dimensional FIR filters are designed for image Denoising, using binary cat swarm optimization. the results obtained are shown that it performs better than the existing systems.