【作者】 周晓瑜；

【导师】 李春光；

【作者基本信息】 浙江大学 ， 电路与系统， 2012， 硕士

【摘要】 超分辨率(super-resolution)重建是通过图像处理技术从多幅低分辨率图像(low-resolution)中获得一幅高分辨率图像(high-resolution)的过程。已有文献一般在假设位移已知或点扩展函数(PSF)已知的情况下重建SR图像,但很少涉及两者都未知的情况。可在实际情况中,能够得到的往往只是同一场景的多幅图像数据,而位移和PSF都是未知的。在这种情况下,如何重建出一幅高分辨率图像便是本论文要解决的问题。本论文提出了一种新型实用的基于未知位移和未知PSF的SR重建方法。我们首先利用LR (low-resolution)图像帧内像素点的相关性,再利用块匹配算法获得亚像素点位移估计。然后在选择了ML算法进行盲解卷积。本论文最大的特点是除了需要低分辨率图像数据外,不需要额外的先验知识,而且提出的解决SR重建问题的方法在位移估计和盲解卷积上采用了简单易用的方法,整体方法计算复杂度低,实用性强。在仿真结果上,得到了较好的重建效果。由于SR重建问题往往并不是由一个单一算法就能够解决的问题,常常是需要一个整体的解决方案,因此,为了获得良好的重建效果,本论文详细地分析比较了各种可能用于SR重建问题的方法,具体的如统计方法,图像处理方法,优化算法等,其中对于运动估计,比较了常用的几类估计方法,从中选择了块匹配算法。对于盲解卷积方法,同样比较了几种可用的方法,并从中选择了一种计算简单,应用方便的盲解卷积方法。此外,为了更好地适应于快速SR重建问题,我们也对一些方法进行了改进,如在运动估计和盲解卷积方法上,我们对相应算法做了改进,使其能在计算上效率更高,使重建效果更好。更多还原

【Abstract】 SR (super-resolution) reconstruction is a restoring method which makes use of a series of LR images to restore an HR image based on image processing technology. Several common SR methods are analyzed. In literature, the motion or PSF (point spread function) is generally supposed as known. However, less study considers the case that both of them are unknown. However, in a real situation, there is only image data and the motion and PSF are unknown. In this situation, how to reconstruct HR image is the key problem the paper deals with. In this paper, a useful SR reconstruction method for unknown global translation and unknown PSF is proposed. For motion estimation, the relation of pixels in an LR (low-resolution) image is used to realize the sub-pixel translation estimation and for specific estimation algorithm, the easily used block-matching algorithm is chosen. For unknown PSF, the necessity of blind deconvolution is discussed. Since ML algorithm is less constraint, it is chosen for blind deconvolution. The outstanding characteristic of the paper is that the only necessity for SR construction is the LR image data showing the same scene. Besides, the SR method proposed is easily applied with less computing complexity. The simulation results have been presented to show the effectiveness of the proposed algorithm.Since the problem of SR reconstruction is unable to be solved by one method, an overall approach is usually needed. Thus in order to improve the restoring efficiency and restoring effect, a lot of methods which are able to be used in SR reconstruction are discussed and compared, such as statistical methods, image processing methods and optimization algorithm etc. Specifically for motion estimation, block matching method is chosen after several motion estimation methods discussed and for blind deconvolution method, a convenient method is chosen from several blind deconvolution methods.Besides, several existing methods are improved in order to reconstruct HR image faster and better. For example, in motion estimate and blind deconvolution, we have improved the existing algorithms, which enhance the efficiency of reconstruction.更多还原