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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(More)
In the area of content-based image retrieval, the feature-matching algorithm based on color histogram intersection ignores the similarity of different color. In order to solve this problem, this paper presents a new image-matching algorithm based on sphere similarity of color histogram intersection in the GRB space. The experimental results show that the(More)
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