A Novel Filtering Scheme for Impulse Noise Cancellation

Abstract

This paper proposes a novel filtering scheme to denoise images contaminated by impulse noise of high densities. This scheme utilizes two stage operations. In the first stage, corrupted image is passed through the Artificial Neural Network (ANN) detector to identify the noisy pixels by considering their surrounding neighborhood. The corrupted pixels are passed through the Discrete Wavelet Transform (DWT) based pre-filter and the filtered pixels are replaced back in the image. The pre-filtered image is further passed through the ANN detector to capture any residual corruption. A novel selective spatial filtering scheme is proposed for the corrupted pixels. The proposed scheme is simulated using standard images under different noise conditions. The comparative performance study shows the superiority of the proposed scheme over the existing standard filtering schemes both in terms of noise rejection and edge retention capability even under high noise conditions.