A blind restoration method for blurry images based on noise analysis and sparsity regularization
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Shanghai Maritime University,Shanghai Maritime University,Shanghai Maritime University,Shanghai Maritime University

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    Abstract:

    In the course of maritime search and rescue, infrared image captured by helicopter airborne infrared camera has a poor image quality because of the helicopter vibration, air turbulence, high speed flight and infrared camera sweeping. According to the imaging characteristics of the helicopter airborne infrared camera, a blind restoration method for blurry images based on noise analysis and sparsity regularization was proposed. Firstly, noise distribution in the imaging process is analyzed and the noise is pre-processed. Then, according to the sparse representation theory, sparse prior information of the edges in the images is used to guide the restoration of PSF. After that, we can obtain the target image through non-blind method. The target image will be used in the next iteration. The iteration will not end until a clear image is obtained. Experiments were performed both on simulated blurry images and real blurry images. Experimental results show that our method can effectively improve the image quality.Compared with other methods, our method has a better effect on real blurry images.

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KANG Zhi-Li, AN Bo-Wen, PAN Sheng-Da, ZHAO Ming. A blind restoration method for blurry images based on noise analysis and sparsity regularization[J]. Journal of Infrared and Millimeter Waves,2017,36(3):376~382

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History
  • Received:August 08,2016
  • Revised:September 25,2016
  • Adopted:September 27,2016
  • Online: March 28,2017
  • Published: