The classification of hyperspectral data by means of per pixel classifiers forces each mixed pixel to map onto a single class, whereas sub-pixel classifiers are incapable of spatial arrangement of the land cover classes at its sub-pixel level. Super resolution mapping technique takes advantage of fractional abundance of each pixel and its surrounding pixels to make the classified image much finer spatial resolution. The pixel to be super resolved (PTS) is divided into equal number of rows and columns, according to pre-defined zoom factor. The spatial proximity of the pixel is also considered in mapping at the sub-pixel level of the hyperspectral data. Now, each sub-pixel of the PTS is modelled as linear combination of number of sub-pixels allotted to the neighbouring pixels with pre-defined weights, and here they are 8 and 17, which directly depend upon the spatial location or proximity of the sub-pixels of PTS and neighbouring pixels. Irrespective of the sizes of the classes, all classes are treated equal while filling the sub-pixels in that PTS, which preserves small classes or targets of the image. Experiments have been carried out on a synthetic data and two hyperspectral datasets of different nature. The overall accuracy of super resolution mapping for synthetic data comes to be 96.3% for the whole image, while the accuracy for super resolved of only mixed pixels comes to be 86.3%. Further, experiments on real hyperspectral datasets have been carried out, and the overall accuracy comes to be more than 95% for both the datasets.

中文翻译：

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基于像素填充算法的高光谱图像空间分辨率增强映射

通过逐像素分类器对高光谱数据进行分类迫使每个混合像素映射到单个类上，而子像素分类器无法在其子像素级别对土地覆盖类进行空间排列。超分辨率映射技术利用每个像素及其周围像素的分数丰度，使分类图像具有更精细的空间分辨率。根据预定义的缩放系数，要超分辨 (PTS) 的像素被分成相等数量的行和列。在高光谱数据的子像素级别的映射中也考虑了像素的空间接近度。现在，PTS 的每个子像素都被建模为分配给具有预定义权重的相邻像素的子像素数量的线性组合，这里它们是 8 和 17，这直接取决于 PTS 和相邻像素的子像素的空间位置或接近度。无论类的大小如何，在填充该 PTS 中的子像素时，所有类都被同等对待，从而保留了图像的小类或目标。已经对合成数据和两个不同性质的高光谱数据集进行了实验。合成数据的超分辨率映射对整幅图像的整体准确率为 96.3%，而仅混合像素的超分辨率的准确率为 86.3%。此外，已经在真实的高光谱数据集上进行了实验，两个数据集的整体准确率都超过了 95%。在填充该 PTS 中的子像素时，所有类都被平等对待，从而保留了图像的小类或目标。已经对合成数据和两个不同性质的高光谱数据集进行了实验。合成数据的超分辨率映射对整幅图像的整体准确率为 96.3%，而仅混合像素的超分辨率的准确率为 86.3%。此外，已经在真实的高光谱数据集上进行了实验，两个数据集的整体准确率都超过了 95%。在填充该 PTS 中的子像素时，所有类都被平等对待，从而保留了图像的小类或目标。已经对合成数据和两个不同性质的高光谱数据集进行了实验。合成数据的超分辨率映射对整幅图像的整体准确率为 96.3%，而仅混合像素的超分辨率的准确率为 86.3%。此外，已经在真实的高光谱数据集上进行了实验，两个数据集的整体准确率都超过了 95%。合成数据的超分辨率映射对整幅图像的整体准确率为 96.3%，而仅混合像素的超分辨率的准确率为 86.3%。此外，已经在真实的高光谱数据集上进行了实验，两个数据集的整体准确率都超过了 95%。合成数据的超分辨率映射对整幅图像的整体准确率为 96.3%，而仅混合像素的超分辨率的准确率为 86.3%。此外，已经在真实的高光谱数据集上进行了实验，两个数据集的整体准确率都超过了 95%。