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A novel hyperspectral images destriping method based on edge reconstruction and adaptive morphological operators

机译:基于边缘重构和自适应形态运算符的新型高光谱图像消除方法

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In recent years, the specialized destriping methods for remote-sensing image emphasize efficiency and flexibility but lose the particulars in wide stripes. Though many excellent inpainting algorithms have been proposed, most of them are too complex and inefficient for hyperspectral image (HSI). In this paper, we propose a novel automatic completing method which is appropriate for the feature of HSI and easy to be implemented in parallel. The boundary information in broken region is restored primarily based on SVM with the input of the surrounding detected edges. Then we introduce an adaptive morphological filling operator restrained by the boundaries to estimate the pixels in the same position of all bands synchronously. Experimental results show satisfactory performance of the proposed system and its significance on HSI completion.
机译:近年来,用于遥感图像的专业腐蚀方法强调效率和灵活性,但丢失了宽条纹的细节。 虽然已经提出了许多优异的初始算法,但对于高光谱图像(HSI)而言,大多数太复杂并且效率低。 在本文中,我们提出了一种新的自动完成方法,适用于HSI的特征,易于并行实现。 断开区域中的边界信息主要基于SVM,其输入周围检测到的边缘。 然后,我们介绍由边界限制的自适应形态填充算子,以同步估计所有频带的相同位置的像素。 实验结果表明,拟议的系统令人满意的表现及其对HSI完成的重要性。

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