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RECONSTRUCTION OF MISSING DATA IN VHR IMAGES USING BANDELET AND EXEMPLAR BASED INPAINTING STRATEGIES

机译:使用基于条带和示例的插入策略重建VHR图像中的缺失数据

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The process of inpainting is to reconstruct the lost or deteriorated parts of images.The reconstruction of missing data in very high spatial remote sensed image is of great challenge due to its complexity. Remotely sensed Very High Resolution (VHR) images may be partly contaminated by cloud and accurate reconstruction of such images is of great problem.In this paper two strategies were proposed one for cloud removal and other for reconstruction of missing regions to improve the accuracy.The cloud removal problem is achieved by means of bandelet transform and multiscale geometrical grouping algorithm.This algorithm aims at removing the cloud contaminated portions from the VHR images.Then Exemplar based inpainting strategy (approach) is used for reconstruction of missing regions.The two algorithms used here are very simple and efficient results can be obtained.
机译:修复的过程是重建图像的丢失或退化部分。由于空间复杂度高,在非常高的空间遥感图像中丢失数据的重建面临很大的挑战。遥感超高分辨率(VHR)图像可能会被云部分污染,因此此类图像的准确重建是一个很大的问题。本文提出了两种策略:一种用于云去除,另一种用于缺失区域的重建,以提高准确性。借助bandelet变换和多尺度几何分组算法解决了云去除问题,该算法旨在从VHR图像中去除云污染部分,然后将基于样例的修复策略(方法)用于缺失区域的重建,使用了两种算法这是非常简单有效的结果。

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