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首页> 外文会议>IEEE International Conference on Information and Automation >Blind Image Super-Resolution Reconstruction Based on PSF Estimation
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Blind Image Super-Resolution Reconstruction Based on PSF Estimation

机译：基于PSF估计的盲目图像超分辨率重建

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摘要

Blind image super-resolution reconstruction is one of the challenges in image restoration. In order to improve the spatial resolution of low resolution images, a blind image super-resolution reconstruction method is proposed. The point spread function (PSF) of the imaging system is estimated to approximate the low-resolution imaging model much more accurately. An error-parameter analysis method is proposed to estimate the parameters of Gaussian PSF. Utilizing Wiener filtering image restoration algorithm, multiple curves are generated at different parameters. By setting some thresholds, the size and deviation of the Gaussian PSF can be estimated automatically. The experimental results show that this algorithm achieves high precision, and validates the great importance of PSF estimation in image super resolution reconstruction. The experimental results demonstrate the effectiveness of the proposed algorithm.
机译：盲目图像超分辨率重建是图像恢复中的挑战之一。为了提高低分辨率图像的空间分辨率，提出了一种盲图像超分辨率重建方法。估计成像系统的点扩展功能（PSF）以更准确地近似低分辨率成像模型。提出了一个错误参数分析方法来估计高斯PSF的参数。利用Wiener滤波图像恢复算法，在不同的参数下产生多条曲线。通过设置一些阈值，可以自动估计高斯PSF的大小和偏差。实验结果表明，该算法高精度，验证了图像超分辨率重建中PSF估计的重要性。实验结果表明了所提出的算法的有效性。

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