Osama A. Omer

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In a typical superresolution algorithm, fusion error modeling, including registration error and additive noise, has a great influence on the performance of the super-resolution algorithms. In this letter, we show that the quality of the reconstructed high-resolution image can be increased by exploiting proper model for the fusion error. To properly model(More)
In this paper we propose an efficient modification for the Horn-Schunck optical flow estimation algorithm. The proposed modification is represented by incorporating the segmentation with the optical flow estimation in two-stage optical flow estimation. In the first stage, a reference image is segmented into homogeneous regions. In the second stage, the(More)
A fast and effective iterative demosaicking algorithm is described for reconstructing a full-color image from single-color filter array data. The missing color values are interpolated on the basis of optimization and projection in different frequency bands. A filter bank is used to decompose an initially interpolated image into low-frequency and(More)
We address problems of conventional super-resolution (SR) methods having the following limitations. First, most of the existing SR algorithms can not cope with local motions and hence not suitable for video sequences. Second, the blurring operator is assumed to be known in advance and constant for all the low-resolution (LR) images. Finally, SR noise is(More)