Remote sensing based on hyperspectral data analysis
نویسنده
چکیده
منابع مشابه
Overlap-based feature weighting: The feature extraction of Hyperspectral remote sensing imagery
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...
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Hyperspectral Imagery Sensing (HIS) is widely gained tremendous popularity in many research areas such as remotely sensed satellite imaging and aerial reconnaissance. HIS is an important technique with the measurement, analysis, and interpretation of spectra acquired sensing scene an airborne or satellite sensor. The development of sensor technology brought the developing of collecting image da...
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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...
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The ability of recording the high resolution spectral signature of earth surface would be the most important feature of hyperspectral sensors. On the other hand, classification of hyperspectral imagery is known as one of the methods to extracting information from these remote sensing data sources. Despite the high potential of hyperspectral images in the information content point of view, there...
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Remote sensing image analysis can be carried out at the per-pixel (hard) and sub-pixel (soft) scales. The former refers to the purity of image pixels, while the latter refers to the mixed spectra resulting from all objects composing of the image pixels. The spectral unmixing methods have been developed to decompose mixed spectra. Data-driven unmixing algorithms utilize the reference data called...
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The earth is continually being influenced by some actions such as flood, tornado and human artificial activities. This process causes the changes in land cover type. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes. Today’s remote sensing plays key role in geology and environmental monitoring by its high resolution, wide covering and low cost...
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