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Adaptive weighted undersampling image reconstruction algorithm


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Adaptive weighted undersampling image reconstruction algorithm
Ban XiaozhengLi Zhihua
School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China
compressed sensing image reconstruction iterative support detection adaptive weighted
Aiming at the problem that TV regularized image reconstruction is easy to be sensitive to noise and artifacts in under-sampling environment,a dual regularized adaptive weighted image reconstruction model combining the discrete wavelet and the TV is constructed. Based on this model,an adaptive weighted iterative reconstruction algorithm is proposed. In each iteration,the algorithm calculates the TV regularization term and the wavelet coefficient prior term by the threshold shrinkage method,and then updates the reconstructed image. In order to improve the quality of the reconstructed image,an iterative support detection method is introduced to calculate the adaptive weight of the wavelet coefficient. The experimental results show that the proposed algorithm can achieve better overall performance in terms of time efficiency and reconstruction quality than other similar algorithms.


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Last Update: 2020-04-20