A new fusion of mutual information and Otsu multilevel thresholding technique for hyperspectral band selection
نویسندگان
چکیده
منابع مشابه
Spatial Mutual Information Based Hyperspectral Band Selection for Classification
The amount of information involved in hyperspectral imaging is large. Hyperspectral band selection is a popular method for reducing dimensionality. Several information based measures such as mutual information have been proposed to reduce information redundancy among spectral bands. Unfortunately, mutual information does not take into account the spatial dependency between adjacent pixels in im...
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The multilevel thresholding problem is a challenge task due to the fact that the computation is usually very time-consuming for obtaining the optimal multilevel thresholds. Though the state-of-the-art multilevel thresholding algorithms applied various meta-heuristic techniques or acceleration strategies, they still directly searched the optimal thresholds in the whole histogram only for the fix...
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in recent years, sub-band speech recognition has been found useful in addressing the need for robustness in speech recognition, especially for the speech contaminated by band-limited noise. in sub-band speech recognition, the full band speech is divided into several frequency sub-bands, with the result of the recognition task given by the combination of the sub-band feature vectors or their lik...
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Hyperspectral band image selection is a fundamental problem for hyperspectral remote sensing data processing. Accepting its importance, several information-based band selection methods have been proposed, which apply Shannon entropy to measure image information. However, the Shannon entropy is not accurate in measuring image information since it neglects the spatial distribution of pixels and i...
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ژورنال
عنوان ژورنال: Egyptian Informatics Journal
سال: 2021
ISSN: 1110-8665
DOI: 10.1016/j.eij.2020.06.002