Yuqing Zhao, Guangyuan Fu, Hongqiao Wang, Shaolei Zhang, Min Yue
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引用次数: 3
Abstract
Blind deblurring of a single infrared image is a challenging computer vision problem. Because the blur is not only caused by the motion of different objects but also by the relative motion and jitter of cameras, there is a change of scene depth. In this work, a method based on the GAN and channel prior discrimination is proposed for infrared image deblurring. Different from the previous work, we combine the traditional blind deblurring method and the blind deblurring method based on the learning method, and uniform and nonuniform blurred images are considered, respectively. By training the proposed model on different datasets, it is proved that the proposed method achieves competitive performance in terms of deblurring quality (objective and subjective).
期刊介绍:
International Journal of Optics publishes papers on the nature of light, its properties and behaviours, and its interaction with matter. The journal considers both fundamental and highly applied studies, especially those that promise technological solutions for the next generation of systems and devices. As well as original research, International Journal of Optics also publishes focused review articles that examine the state of the art, identify emerging trends, and suggest future directions for developing fields.