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DE-STRIPING FOR TDICCD REMOTE SENSING IMAGE BASED ON STATISTICAL FEATURES OF HISTOGRAM

机译:基于直方图的统计特征的TDICCD遥感图像的去条带

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Aim to striping noise brought by non-uniform response of remote sensing TDI CCD, a novel de-striping method based on statistical features of image histogram is put forward. By analysing the distribution of histograms, the centroid of histogram is selected to be an eigenvalue representing uniformity of ground objects, histogrammic centroid of whole image and each pixels are calculated first, the differences between them are regard as rough correction coefficients, then in order to avoid the sensitivity caused by single parameter and considering the strong continuity and pertinence of ground objects between two adjacent pixels, correlation coefficient of the histograms is introduces to reflect the similarities between them, fine correction coefficient is obtained by searching around the rough correction coefficient, additionally, in view of the influence of bright cloud on histogram, an automatic cloud detection based on multi-feature including grey level, texture, fractal dimension and edge is used to pre-process image. Two 0-level panchromatic images of SJ-9A satellite with obvious strip noise are processed by proposed method to evaluate the performance, results show that the visual quality of images are improved because the strip noise is entirely removed, we quantitatively analyse the result by calculating the non-uniformity, which has reached about 1% and is better than histogram matching method.
机译:提出了一种基于图像直方图的统计特征的非均匀响应所带来的噪声。通过分析直方图的分布,选择直方图的质心是表示地面对象均匀性的特征值,首先计算整个图像的直方图和每个像素,它们之间的差异是粗糙校正系数,然后是为了避免单个参数引起的灵敏度,并且考虑到两个相邻像素之间的接地对象的强连续性和解决方案,直方图的相关系数介绍以反映它们之间的相似性,通过围绕粗糙校正系数来搜索微量校正系数,另外鉴于明亮云对直方图的影响,基于多种功能的自动云检测包括灰度,纹理,分形维数和边缘,用于预处理图像。通过提出的方法处理具有明显的条带噪声的SJ-9A卫星的两个0级Panchromic图像,以评估性能,结果表明图像的视觉质量得到改善,因为条带噪声完全被移除,我们通过计算来定量分析结果不均匀性,其达到约1%并且优于直方图匹配方法。

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