天文图像的稀疏表示
Sparse Representation of Astronomical Images
摘要：
讨论了天文图像的稀疏表示问题。结果表明，当特定的混合字典用于近似这些类型的图像与贪婪的选择策略时，实现了显着的稀疏增益。进行实验以确认：i）产生稀疏表示的有效性。ii）在处理大图像所需的时间方面具有竞争力。后者是所提出的字典在小块分区中近似图像的适用性的结果。这个功能使得可以应用有效的贪婪选择技术正交匹配追踪，直到一些块大小。对于超过该大小的块，考虑原始匹配追踪方法的改进。由此产生的方法被称为自投影匹配追踪，因为被证明是有效的实施，通过匹配追踪本身，在该方法中的可选的反投影中间步骤。
英文摘要：
Sparse representation of astronomical images is discussed. It is shown that a significant gain in sparsity is achieved when particular mixed dictionaries are used for approximating these types of images with greedy selection strategies. Experiments are conducted to confirm: i)Effectiveness at producing sparse representations. ii)Competitiveness, with respect to the time required to process large images.The latter is a consequence of the suitability of the proposed dictionaries for approximating images in partitions of small blocks.This feature makes it possible to apply the effective greedy selection technique Orthogonal Matching Pursuit, up to some block size. For blocks exceeding that size a refinement of the original Matching Pursuit approach is considered. The resulting method is termed Self Projected Matching Pursuit, because is shown to be effective for implementing, via Matching Pursuit itself, the optional back-projection intermediate steps in that approach.
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