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We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is represented as a deep convolutional neural...

Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of t...

In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinatio...

Multiresolution representations are effective for analyzing the information content of images. The properties of the operator which approximates a signal at a given resolution were studied. It is shown that the differenc...

Suppose x is an unknown vector in Ropf m (a digital image or signal); we plan to measure n general linear functionals of x and then reconstruct. If x is known to be compressible by transform coding with a known transform...

Materias / palabras clave: image processing, image enhancement, image analysis, image coding and transmission, multimedia; Technology: Photography; Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer so...

Materias / palabras clave: image acquisition, image analysis, image coding, image interpretation, image retrieval, image transmission; Technology: Photography

Materias / palabras clave: intelligent video analysis, diffractive optics, image analysis, information coding, hyperspectral data analysis, image processing; Science: Science (General): Cybernetics: Information theory; Science: Physics: Optics. Li...