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Improvement in image resolution based on dispersive representation of data

机译:基于数据分散表示的图像分辨率提高

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A method for reconstructing the resolution of images, based on selection and optimization of significant local features and sparse representation of processed-image blocks (using optimized low- and high-resolution dictionaries), has been substantiated for the first time. This method, making it possible to improve significantly the resolution of images of various nature, is interpreted physically. A block diagram of the processing system corresponding to the new approach to image reconstruction has been developed. A simulation of the new method for reconstructing images of different physical natures and known algorithms showed an advantage of the new scheme for reconstructing resolution in terms of universally recognized criteria (peak signal-to-noise ratio, mean absolute error, and structural similarity index measure) and in visual comparison of the processed images.
机译:首次证实了一种基于重要局部特征的选择和优化以及已处理图像块的稀疏表示(使用优化的低分辨率和高分辨率字典)的重构图像分辨率的方法。物理上解释了这种方法,使得可以显着提高各种性质的图像的分辨率。已经开发了与图像重建的新方法相对应的处理系统的框图。对重构不同物理性质的图像的新方法和已知算法的仿真显示,该重构方案在普遍公认的标准(峰值信噪比,平均绝对误差和结构相似性指标度量)方面具有优势)并在视觉上比较处理后的图像。

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