Multichannel Parallel Deblurring and Collaborative Registration Using Gaussian Total Variation Regularization for Image Fusion

Shiping Guo, Hongqiang Lv, Yongyi Liu, Rongzhi Zhang and Jisheng Li

Mathematical Problems in Engineering, 2016, vol. 2016, 1-10

Abstract:

We focus on the multichannel image fusion problem for the purpose of reaching the diffraction-limited resolution of turbulence-degraded images observed by multiple acquisition channels. A hybrid strategy consisting of multichannel parallel deblurring followed by collaborative registration is developed for the final fusion. In particular, a Gaussian total variation regularization scheme taking advantage of low-order Gaussian derivative operators is proposed, which integrates the deblurring and registration problems into a unified mathematical formalization. Specifically, the gradient magnitude of Gaussian operator is proposed to define the total variation norm, and the Laplacian of Gaussian operator is used to adjust the regularization parameter when searching the extremum in each iterative step. In addition, the coordination technique involving the regularization parameter among different channels is also considered.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:9491326

DOI: 10.1155/2016/9491326

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