エッジの強度と方向に基づく画像内挿手法

Abstract

Super-resolution is recently one of the most attractive research themes in the field of digital image processing. Forexample, it is used for high-resolution display, visual sensing, and satellite image processing, etc. An image in terpolation method using covariance between neighboring pixels, so called New Edge-Directed Interpolation (NEDI), was been proposed. It enables to interpolate pixels quantitatively regardless of edge features. However, in estimation of predictive coefficients and determination of NEDI's local window size, edge features are not made consideration. So, NEDI cannot necessarily satisfy quality of picture. In order to overcome this problem, we propose a new infra-frame super-resolution method that window sizes are adaptively determined depending on edge strengths and orientations. First, we detect edge and its strength in an image, and set NEDI's applicable area and local window size depending on the detected edge strength. If the detected edge strength is intensive, we set local window size small and set applicable are anarrow. Using these features, we estimate predictive coefficients, and interpolate pixels. Experimental simulation shows that the proposed method can interpolate pixels more clearly than NEDI for many kinds of edges. We are going to automate setting interpolation parameters and modify in terpolation in non-edgea rea.