Given that the existing nonuniformity correction algorithms still struggle to achieve low noise images, good real-time performance, and more texture details, a shearlet deep neural network from the perspective of transforming domain is put forward in the paper. The proposed method uses the non-subsampled shearlet transform to track the stripe noise. And then defines the regularization method according to the features extracted by the shearlet to help restore the image details. The experiments based on simulation datasets and real datasets show that the proposed method is superior to several classical denoising algorithms in quantitative and qualitative evaluation.
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