基于改进Criminisi算法的地基云图修复方法

全天空成像仪（Total sky imager,TSI）对天空进行观测时,设备的结构特点会使采集到的云图信息不完整,对图像的分析造成不利影响。针对Criminisi算法修复地基云图所造成修复顺序发生错误、图像不连续以及匹配块遍历搜索时间复杂度大的问题,本文提出了一种基于改进Criminisi算法的地基云图修复方法。该算法改进了优先权计算公式,引入地基云图独特的红蓝比特征作为置信项,使得含有更多信息的像素块具有更高的优先级,在搜索匹配块的过程中,基于启发信息选择匹配区域的大小,避免了搜索到离待修复块较远的相关性较低的匹配块,也有效缩短了匹配块搜索时间,降低了算法的时间复杂度。实验结果表明,改进后的Criminisi算法具有较好的图像修复效果,且降低了时间复杂度,提高了修复效率。

Ground-Based Cloud Image Inpainting Method Based on Improved CriminisiAlgorithm

When the total sky imager (TSI) is used to observe the sky, the structural characteristics of the device will make the collected cloud image information incomplete, which affects the analysis of images. In order to deal with the problems, including the wrong order due to the sharp decrease to zero of the confidence level, the discontinuity of image and the large complexity of time for traversal searching the matching block in the process of repairing ground-based cloud image by the Criminisi algorithm, we propose a ground-based cloud image inpainting method based on the improved Criminisi algorithm in this paper. The calculation formula of priority is improved, and the unique red-blue ratio feature of the ground-based cloud map is introduced as a confidence term, so that the pixel block with more information has higher priority. In the process of searching for the matching block, the searching area is selected based on heuristic information in order to avoid the blocks far away from the block to be repaired and those with low correlation, which effectively shortens the searching time and reduces the time complexity of the algorithm. Experimental results show that the improved Criminisi algorithm has better image restoration effect, can reduce the time complexity and improve the image inpainting efficiency.