Autocorrelation-based interlaced to progressive format conversion

Abstract

To generate a high resolution image from a low resolution one, interpolation plays a crucial role. However, conventional interpolation methods including edge-based interpolation methods have some drawbacks such as the limited number of edge directions, imprecise edge detection, and inefficient interpolation. To overcome these shortcomings, we propose a new edge-directed interpolation method, which has three aims: various edge directions, reliable edge detection, and outstanding interpolation. Since the number of candidate edge directions in the proposed method is flexible, we can use several edges included in the high resolution image. To accurately determine the edge direction, we use autocorrelation of neighboring pixels for candidate directions based on the duality between a high resolution image and its corresponding low resolution image. For the interpolation step, we utilize a Blackman-Harris windowed-sinc weighted average filter where we use correlation values obtained in the edge detection step as weights. Experimental results show that the proposed method outperforms conventional methods in terms of both the subjective and the objective results.