Composite Video Artifact Removal by Nonlinear Bilateral Filtering

A large number of comb filtering techniques for a national television system committee (NTSC) or phase alternate each line (PAL) color decoding have been researched and developed for the last three decades. Comb filtering can separately obtain the luminance and the quadrature amplitude modulation (QAM) modulated chrominance information from a composite video burst signal (CVBS). However there is a difficulty in extracting the luminance and chrominance components from a composite video image because the cross-talk between them gives undesirable image artifacts. The three-dimensional (3-D) comb filter using spatio-temporal filtering kernel and adaptive two-dimensional (2-D) neuralbased comb-filtering approach was developed to alleviate the dot crawl artifacts; however it shows limitation on color decoding. This paper presents an effective dot crawl artifact reduction algorithm in a composite video signal, in which undesirable dot crawl artifact is significantly reduced without losing fine image details. The proposed composite video artifact removal algorithm filters only detected candidate regions specified by dot crawl artifact decision map. The possible comb-filtering error region is generated on video image using luminance and chrominance edge information. Simulation and analysis show that the proposed algorithm with nonlinear bilateral filtering removes efficiently the dot crawl artifacts on composite video image and supports improving further video enhancement techniques.