Spatial pattern discovery for hyperspectral images based on multiresolution analysis

Mario Beauchemin

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Spatial pattern discovery for hyperspectral images based on multiresolution analysis

机译：基于多分辨率分析的高光谱图像空间模式发现

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摘要

A method to discover spatial patterns that are dominant or unique in each spectral band of a hyperspectral image is presented. The approach relies on the multiresolution image fusion framework as well as on exploratory visual data analysis. It is shown that the proportion of dominant details obtained from multiresolution decomposition, and their reconstructed spatial signature, provides valuable clues for image interpretation.

机译：提出了一种发现在高光谱图像的每个光谱带中占主导或唯一的空间模式的方法。该方法依赖于多分辨率图像融合框架以及探索性视觉数据分析。结果表明，从多分辨率分解中获得的主要细节的比例及其重构的空间特征，为图像解释提供了有价值的线索。

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《International journal of image and data fusion》 |2012年第1期|p.93-110|共18页
作者
Mario Beauchemin;
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作者单位

Natural Resources Canada, Canada Centre for Remote Sensing,588 Booth Street, Ottawa, ON K1A 0Y7, Canada;

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原文格式 PDF
正文语种 eng
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关键词
data fusion; wavelet transforms; visualisation; information mining; image analysis; spatial patterns;

机译：数据融合;小波变换可视化信息挖掘;图像分析;空间格局;

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1. Fusion of High Spatial and Spectral Resolution Images Based on Spatial Domain and Multiresolution Analysis [J] . Kavita Tewari, Leena Shah International Journal of Computer Science and Communication Networks . 2012,第03期

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2. Fusion of hyperspectral and panchromatic images using multiresolution analysis and nonlinear PCA band reduction [J] . Giorgio Antonino Licciardi, Muhammad Murtaza Khan, Jocelyn Chanussot, EURASIP journal on advances in signal processing . 2012,第1期

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3. Discovery of novel biomarkers based on spatial immune cell patterns: A disease-overarching image mining approach bridging biopsy evaluation in oncoimmunology and transplantation medicine [J] . Schoenmeyer R., Schaadt N. S., Schaepe A., European journal of cancer: official journal for European Organization for Research and Treatment of Cancer (EORTC) [and] European Association for Cancer Research (EACR) . 2016,第Suppla1期

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Spatial pattern discovery for hyperspectral images based on multiresolution analysis

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