Adaptive Algorithm in Image Reconstruction Based on Information Geometry

• Meng Wang,
• Zhen Hu Ning,
• Jing Yu,
• Chuang Bai Xiao,

Vol. 15, No. 2, February 28, 2021
10.3837/tiis.2021.02.005, Download Paper (Free):

• Information Geometry
• Image Reconstruction
• Compressed sensing

Abstract

Compressed sensing in image reconstruction has attracted attention and many studies are proposed. As we know, adding prior knowledge about the distribution of the support on the original signal to CS can improve the quality of reconstruction. However, it is still difficult for a recovery framework adjusts its strategy for exploiting the prior knowledge efficiently according to the current estimated signals in serial iterations. With the theory of information geometry, we propose an adaptive strategy based on the current estimated signal in each iteration of the recovery. We also improve the performance of existing algorithms through the adaptive strategy for exploiting the prior knowledge according to the current estimated signal. Simulations are presented to validate the results. In the end, we also show the application of the model in the image.

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