A Nonlinear Decision-Based Algorithm for Removal of Strip Lines, Drop Lines, Blotches, Band Missing and Impulses in Images and Videos

Abstract

Abstract A decision-based nonlinear algorithm for removal of strip lines, drop lines, blotches, band missing, and impulses in images is presented. The algorithm performs two simultaneous operations, namely, detection of corrupted pixels and estimation of new pixels for replacing the corrupted pixels. Removal of these artifacts is achieved without damaging edges and details. The algorithm uses an adaptive length window whose maximum size is to avoid blurring due to large window sizes. However, the restricted window size renders median operation less effective whenever noise is excessive in which case the proposed algorithm automatically switches to mean filtering. The performance of the algorithm is analyzed in terms of mean square error [MSE], peak-signal-to-noise ratio [PSNR], and image enhancement factor [IEF] and compared with standard algorithms already in use. Improved performance of the proposed algorithm is demonstrated. The advantage of the proposed algorithm is that a single algorithm can replace several independent algorithms required for removal of different artifacts.