Two-stage False Contour Detection Algorithm Using Re-quantization and Directional Contrast Features and Its Application to Adaptive False Contour Reduction

Abstract

This paper proposes a two-stage false contour detection algorithm using re-quantization and directional contrast features, with application to false contour reduction. In the first stage of false contour detection, smooth regions are first removed by bit-depth reduction and re-quantization. In the second stage, false contours are separated from edge or texture regions using directional contrast features, yielding the false contour detection map that shows possible candidate regions of false contours. For false contour reduction, adaptive directional smoothing filtering is applied only to candidate regions that are specified by the false contour detection map. Therefore the proposed algorithm is able to preserve sharp edges and details. Computer simulation with a large number of test images shows the effectiveness of the proposed algorithm.