نتایج جستجو برای: Hyperspectral
تعداد نتایج: 10793 فیلتر نتایج به سال:
hyperspectral sensors provide a large number of spectral bands. this massive and complex data structure of hyperspectral images presents a challenge to traditional data processing techniques. therefore, reducing the dimensionality of hyperspectral images without losing important information is a very important issue for the remote sensing community. we propose to use overlap-based feature weigh...
Hyperspectral anomaly detection is one of the main challenging topics in both military and civilian fields. The spectral information contained in a hyperspectral cube provides a high ability for anomaly detection. In addition, the costly spatial information of adjacent pixels such as texture can also improve the discrimination between anomalous targets and background. Most studies miss the wort...
Hyperspectral sensors provide a large number of spectral bands. This massive and complex data structure of hyperspectral images presents a challenge to traditional data processing techniques. Therefore, reducing the dimensionality of hyperspectral images without losing important information is a very important issue for the remote sensing community. We propose to use overlap-based feature weigh...
Unmixing of remote-sensing data using nonnegative matrix factorization has been considered recently. To improve performance, additional constraints are added to the cost function. The main challenge is to introduce constraints that lead to better results for unmixing. Correlation between bands of Hyperspectral images is the problem that is paid less attention to it in the unmixing algorithms. I...
Hyperspectral sensors are important tools in monitoring the phenomena of the Earth due to the acquisition of a large number of spectral bands. Hyperspectral image classification is one of the most important fields of hyperspectral data processing, and so far there have been many attempts to increase its accuracy. Spatial features are important due to their ability to increase classification acc...
Hyperspectral imaging with gathering hundreds spectral bands from the surface of the Earth allows us to separate materials with similar spectrum. Hyperspectral images can be used in many applications such as land chemical and physical parameter estimation, classification, target detection, unmixing, and so on. Among these applications, classification is especially interested. A hyperspectral im...
hyperion hyperspectral data contains a very rich source of information from the earth surface that collects 242 narrow contiguous spectral bands. achieving this source of rich information is subject to the performance of suitable image processing methods on raw satellite data. satellite image processing methods can be classified into two categories of statistical-based and spectral-based. in th...
Many researches have demonstrated that the spatial information can play an important role in the classification of hyperspectral imagery. This study proposes a modified spectral–spatial classification approach for improving the spectral–spatial classification of hyperspectral images. In the proposed method ten spatial/texture features, using mean, standard deviation, contrast, homogeneity, corr...
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 Hyperspectral Imagery Compression: State of the Art. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 Outline of This Chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....
the reflectance spectrum of green leaves is considerably affected by their biochemical and biophysical properties. it is possible to extract biochemical information from a continuous vegetation spectrum produced using hyperspectral sensors. the numerous absorption features present in the vegetation spectrum carry a considerable amount of information related to the content and the structure of t...
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