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The purpose of this paper is to develop an algorithm for denoising images corrupted with additive white Gaussian noise (AWGN) with a view to extract object's boundary. The noise degrades quality of the images and makes interpretations, analysis and segmentation of images harder. A pixel is said to be a boundary pixel if its deleted neighborhood contains at least one point from the object and one point...
This paper presents a neural network-based method for image super-resolution. In this technique, the super-resolution is considered as an ill-posed inverse problem which is solved by minimizing an evaluation function established based on an observation model that closely follows the physical image acquisition process. A Hopfield neural network is created to obtain an optimal solution to the problem...
The recognition accuracy of three face recognition algorithms based on subspace methods (i.e., the eigenfaces approach, the fisherfaces technique, and the probabilistic eigenfaces approach) is tested for different gallery sizes, image resolutions and number of bits per pixel. The same experiments are then repeated for various combinations of these techniques and the performance of these combinations...
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