Performance of Blind Deconvolution and Super Resolution Image Reconstruction
Performance of Blind Deconvolution and Super Resolution Image Reconstruction
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DOI：
10.5220/0006467400690076
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
S. Gohshi;Michikazu Akasu
中科院分区：
文献类型：
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作者：
S. Gohshi;Michikazu Akasu
超分辨率(SR)是一种提高数字图像分辨率的技术。超分辨率图像重建(SRR)是最常用的超分辨率图像重建技术之一。然而，除了SRR之外，还有其他几种技术可以提高图像分辨率。在天文学领域，一种被称为盲解卷积(BD)的技术已被用于处理散焦图像。20世纪70年代，当BD首次被描述时，它被认为不是用于SR的可行候选者。然而，提高分辨率的过程与聚焦图像的过程非常相似。SRR和BD都使用迭代从低分辨率图像创建高质量图像。与SRR相比，BD有一些不足之处。例如，算法有时会产生发散或极限环，这意味着无法获得高分辨率的图像。在这项研究中，我们描述了一种方法，通过模拟来解决阻碍BD获得高分辨率图像的问题，以增加其稳定性。将改进的BD算法的输出与当前的SR技术SRR进行了比较。我们证明了BD技术实际上优于SRR技术。
Super Resolution (SR) is a technique for improving the resolution of digital images. Super Resolution Image Reconstruction (SRR) is one of the most common SR techniques. However, in addition to SRR, there are several other techniques to improve image resolution. A technique called Blind Deconvolution (BD) has been used to process out of focus images in the field of astronomy. When BD was first described, in the 1970s, it was not considered to be a viable candidate to be used for SR. However, the process of improving resolution is very similar to that of focusing images. SRR and BD both use iterations to create a high quality image from low resolution images. Compared with SRR, BD comes with some disadvantages. For example, algorithms sometimes cause divergences or limit cycles which means that the high resolution image cannot be obtained. In this study, we describe a method of fixing the issues that prevent BD from achieving a high-resolution image using simulation to increase its stability. The output from the improved algorithm for BD is compared with the current SR technique, SRR. We show that the BD technique is in fact superior to SRR.