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Improved Block Stagewise Regularized Orthogonal Matching Pursuit Image Reconstruction Method

机译:改进的块分段正则正交匹配追踪图像重建方法

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Traditional methods to signal acquisition need to collect large amounts of redundant data, andthen compress the data to extract useful information, which is inefficient and requires largeamount of storage resources. Compressed sensing (CS) can avoid sampling the redundant data;it obtains the discrete signals at the sampling rate that is lower than the Nyquist sampling rate,and reconstructs the original signal with high probability. Based on CS, Block StagewiseRegularized Orthogonal Matching Pursuit (StROMP) is proposed in this paper to reconstructimages. Simulation results show that the proposed algorithm can effectively reduce the requiredstorage storages and computational complexity, which improves the quality of reconstructedimages in the premise of ensuring a shorter reconstruction time.
机译:传统的信号采集方法需要收集大量的冗余数据,然后对数据进行压缩以提取有用的信息,效率低下,需要大量的存储资源。压缩感知(CS)可以避免对冗余数据进行采样;它以低于奈奎斯特采样率的采样率获得离散信号,并以很高的概率重建原始信号。基于CS,提出了基于块的逐级正则化正交匹配追踪(StROMP)重构图像。仿真结果表明,该算法能有效减少所需的存储量和计算复杂度,在保证重建时间较短的前提下,提高了重建图像的质量。

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