摘要
In order to suppress complex mixing noise in low-illumination images for wide-area search of nighttime sea surface,a model based on total variation(TV)and split Bregman is proposed in this paper.A fidelity term based on L1 norm and a fidelity term based on L2 norm are designed considering the difference between various noise types,and the regularization mixed first-order TV and second-order TV are designed to balance the influence of details information such as texture and edge for sea surface image.The final detection result is obtained by using the high-frequency component solved from L1 norm and the low-frequency component solved from L2 norm through wavelet transform.The experimental results show that the proposed denoising model has perfect denoising performance for artificially degraded and low-illumination images,and the result of image quality assessment index for the denoising image is superior to that of the contrastive models.
In order to suppress complex mixing noise in low-illumination images for wide-area search of nighttime sea surface,a model based on total variation(TV)and split Bregman is proposed in this paper.A fidelity term based on L1 norm and a fidelity term based on L2 norm are designed considering the difference between various noise types,and the regularization mixed first-order TV and second-order TV are designed to balance the influence of details information such as texture and edge for sea surface image.The final detection result is obtained by using the high-frequency component solved from L1 norm and the low-frequency component solved from L2 norm through wavelet transform.The experimental results show that the proposed denoising model has perfect denoising performance for artificially degraded and low-illumination images,and the result of image quality assessment index for the denoising image is superior to that of the contrastive models.
基金
supported by the Major Projects of the Ministry of Science and Technology(No.2016YFB0501202)
the Natural Science Foundation of Jilin Province,China(No.20170101164JC)
