An Efficient Super Resolution Based on Image Dimensionality Reduction Using Accumulative Intensity Gradient
Muhammad Haris*, Kazuhito Sawase*,
Muhammad Rahmat Widyanto**, and Hajime Nobuhara*
*Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
**Computer Science Faculty, University of Indonesia, Depok, West Java, Indonesia
An efficient super resolution algorithm based on edge direction is proposed based on the dimensional reduction of color images and 3 types of edge direction. The basic idea is to reduce image – especially color image – dimensions and to interpolate pixels by using 3 simple edge directions – vertical, horizontal, and diagonal. The proposed algorithm conceivably eliminate more color artifacts than Bicubic. The results of experiments using 30 natural images confirm that PSNR of the proposed method achieve the same quality as Fast Curvature Based Interpolation (FCBI). We confirmed that computation time for the proposed method was 40% shorter for RGB and 20% shorter for grayscale images than the previous fastest method, i.e., FCBI. We show efficient panorama image generation based on the proposed super resolution method as one application of our proposal.
Muhammad Rahmat Widyanto, and Hajime Nobuhara, “An Efficient Super Resolution Based on Image Dimensionality Reduction Using Accumulative Intensity Gradient,” J. Adv. Comput. Intell. Intell. Inform., Vol.18, No.4, pp. 518-528, 2014.
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