Application of Super-Resolution Reconstruction of low-Resolution Image Sequences in Spatial Domain
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Abstract
In the traditional single image restoration problem only a single input image is available for processing. The task of reconstructing super-resolution images from multiple under sampled and degraded images can take advantage of the additional spatiotemporal data available in the image sequence. The principal objective is to process an image so that result is more suitable than the original image for an application. In particular, camera and scene motion lead to frames in the source video sequence containing similar, but not identical information. The additional information available in these frames make possible reconstruction of visually superior frames at higher resolution than that of the original data. This paper deals with the super-resolution reconstruction of masked and compressed gray scale images.
Keywords: Super-Resolution, Image Reconstruction, Spatial Domain, Quantization
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