This paper presents a blind defocus deblurring method that produces high-quality deblurred multispectral images. The high quality is achieved by two means: i) more accurate kernel estimation based on the optics prior by simulating the simple lens imaging, and ii) the gradient-based inter-channel correlation with the reference image generated by the content-adaptive combination of adjacent channels for restoring the latent sharp image. As a result, our method gains the prominence on both effectiveness and efficiency in deblurring defocus multispectral images with very good restoration on the obscure details. The experiments on some multispectral image datasets demonstrate the advantages of our method over state-of-the-art deblurring methods.

中文翻译：

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利用光学和梯度先验技术对多光谱图像进行高质量的盲散焦去模糊

本文提出了一种盲散焦去模糊方法，可以产生高质量的去模糊多光谱图像。高质量是通过以下两种方式实现的：i）通过模拟简单的镜头成像，基于光学先验进行更准确的核估计； ii）基于内容的自适应组合生成的参考图像与基于梯度的通道间相关性相邻通道以恢复潜在的清晰图像。结果，我们的方法在对散焦多光谱图像进行去模糊处理时，在有效性和效率上都获得了突出的关注，并且对模糊细节进行了很好的恢复。在一些多光谱图像数据集上的实验证明了我们的方法优于最新的去模糊方法的优势。