An Example-based Super-Resolution Algorithm for Multi-Spectral Remote Sensing Images
نویسنده
چکیده
This paper proposes an example-based superresolution algorithm for multi-spectral remote sensing images. The underlying idea of this algorithm is to learn a matrix-based implicit prior from a set of high-resolution training examples to model the relation between LR and HR images. The matrixbased implicit prior is learned as a regression operator using conjugate decent method. The direct relation between LR and HR image is obtained from the regression operator and it is used to super-resolve low-resolution multi-spectral remote sensing images. A detailed performance evaluation is carried out to validate the strength of the proposed algorithm. Keywords—Remote sensing Super-resolution; Image-pair analysis; Regression operators
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