False contour reduction using neural networks and adaptive bi-directional smoothing

Abstract

This paper proposes a false contour reduction algorithm using neural networks (NNs) and adaptive bi-directional smoothing. The proposed algorithm consists of two parts: false contour detection and reduction parts. In the false contour detection part, false contour candidate pixels are detected using the directional contrast features. The false contour reduction part is composed of two steps: NN processing and bi-directional filtering. In the first step, false contours are reduced by pixelwise processing using NNs. In the second step, bi-directional smoothing is applied to a neighboring region of the false contour. Computer simulations with several test images show the effectiveness of the proposed false contour reduction algorithm in terms of the visual perception.