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Hyperspectral image super resolution (SR) reconstruction has been studied widely and many algorithms have been proposed. In this paper, a novel super resolution reconstruction method was designed by employing a joint spectral-spatial sub-pixel mapping model which aims to obtain the probabilities of sub-pixels to belong to different land cover classes by dividing mixed pixels into several sub-pixels...
The sub-pixel mapping method, which can provide a resolution-enhanced map in classification has been widely used in remote sensing. To better utilize the spatial information of the image, in this paper, a new sub-pixel mapping algorithm based on non-local means (NLSM) is proposed. In NLSM, the non-local means, which is a regularize term, is used to exploit the similar patterns in fraction images,...
Hyperspectral images (HSIs) provide abundant information to solve various kinds of problems like object identification and classification. However, HSIs often inevitably suffer many factors from various resources [1], such as imperfect imaging optics, sensor noise, and atmospheric effects, which degrade the acquired image quality [2]. Thus, HSI image super resolution reconstruction, used to achieve...
Traditional sub-pixel mapping methods were imposed on the fraction image which was generated with spectral unmixing techniques. Obviously, the capability of sub-pixel mapping was limited by the accuracy of the obtained fraction image. In this paper, a unified sub-pixel mapping model was proposed by integrating the spectral unmixing to implement on the low-resolution hyperspectral imagery directly...
The sub-pixel mapping technique, which can provide a fine-resolution map of class labels, has attracted more and more attention in recent years. Generally speaking, there are two kinds of methods used to realize the sub-pixel labeling. The first kind are image reconstruction based methods, which first improve the spatial resolution of an image by the super-resolution technique, and then perform a...
In this paper, a sub-pixel mapping algorithm based on differential evolution is proposed, namely adaptive differential evolution sub-pixel mapping algorithm (ADESM). In ADESM, the sub-pixel mapping problem becomes one of assigning land cover classes to the sub-pixels while maximizing the spatial dependence index (SDI). In the proposed ADESM algorithm, individuals are represented as a discrete sub-pixel...
In this paper, a new sub-pixel mapping method inspired by the clonal selection algorithm (CSA) in artificial immune systems (AIS) is proposed, namely clonal selection subpixel mapping (CSSM). In CSSM, the sub-pixel mapping problem becomes one of assigning land cover classes to the sub-pixels while maximizing the spatial dependence by clonal selection algorithm. CSSM inherits the biologic properties...
Mixed pixel is a common problem in Remotely Sensed classification. Even though the composition of these pixels for different classes can be estimated with pixel un-mixing model, the output provides no indication of how such classes are distributed spatially within these pixels. Sub-pixel mapping is a technique designed to obtain the spatial distribution of these classes in these pixels with information...
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