Improved interactive color visualization approach for hyperspectral images
Hyperspectral images (HSIs) have become increasingly prominent as they can maintain the subtle spectral differences of the imaged objects. Designing approaches and tools for analyzing HSIs presents a unique set of challenges due to their high-dimensional characteristics. An improved color visualizat...
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Veröffentlicht in: | Information visualization 2022-04, Vol.21 (2), p.153-165 |
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description | Hyperspectral images (HSIs) have become increasingly prominent as they can maintain the subtle spectral differences of the imaged objects. Designing approaches and tools for analyzing HSIs presents a unique set of challenges due to their high-dimensional characteristics. An improved color visualization approach is proposed in this article to achieve communication between users and HSIs in the field of remote sensing. Under the real-time interactive control and color visualization, this approach can help users intuitively obtain the rich information hidden in original HSIs. Using the dimensionality reduction (DR) method based on band selection, high-dimensional HSIs are reduced to low-dimensional images. Through drop-down boxes, users can freely specify images that participate in the combination of RGB channels of the output image. Users can then interactively and independently set the fusion coefficient of each image within an interface based on concentric circles. At the same time, the output image will be calculated and visualized in real time, and the information it reflects will also be different. In this approach, channel combination and fusion coefficient setting are two independent processes, which allows users to interact more flexibly according to their needs. Furthermore, this approach is also applicable for interactive visualization of other types of multi-layer data. |
doi_str_mv | 10.1177/14738716211048142 |
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Designing approaches and tools for analyzing HSIs presents a unique set of challenges due to their high-dimensional characteristics. An improved color visualization approach is proposed in this article to achieve communication between users and HSIs in the field of remote sensing. Under the real-time interactive control and color visualization, this approach can help users intuitively obtain the rich information hidden in original HSIs. Using the dimensionality reduction (DR) method based on band selection, high-dimensional HSIs are reduced to low-dimensional images. Through drop-down boxes, users can freely specify images that participate in the combination of RGB channels of the output image. Users can then interactively and independently set the fusion coefficient of each image within an interface based on concentric circles. At the same time, the output image will be calculated and visualized in real time, and the information it reflects will also be different. In this approach, channel combination and fusion coefficient setting are two independent processes, which allows users to interact more flexibly according to their needs. 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Designing approaches and tools for analyzing HSIs presents a unique set of challenges due to their high-dimensional characteristics. An improved color visualization approach is proposed in this article to achieve communication between users and HSIs in the field of remote sensing. Under the real-time interactive control and color visualization, this approach can help users intuitively obtain the rich information hidden in original HSIs. Using the dimensionality reduction (DR) method based on band selection, high-dimensional HSIs are reduced to low-dimensional images. Through drop-down boxes, users can freely specify images that participate in the combination of RGB channels of the output image. Users can then interactively and independently set the fusion coefficient of each image within an interface based on concentric circles. At the same time, the output image will be calculated and visualized in real time, and the information it reflects will also be different. In this approach, channel combination and fusion coefficient setting are two independent processes, which allows users to interact more flexibly according to their needs. Furthermore, this approach is also applicable for interactive visualization of other types of multi-layer data.</description><subject>Color</subject><subject>Hyperspectral imaging</subject><subject>Interactive control</subject><subject>Multilayers</subject><subject>Real time</subject><subject>Remote sensing</subject><subject>Visualization</subject><issn>1473-8716</issn><issn>1473-8724</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1UEtLAzEQDqJgrf4Abwuet2aSNEmPUnxUCl70vAzJxG7Zdtdkt1B_vSkVPYinGeZ7zDfD2DXwCYAxt6CMtAa0AODKghInbHSYldYIdfrTgz5nFymtORdG8dmIPS82XWx35It621NE19c7KlzbtLHY1WnApv7Evm63BXaZiG5VhAyt9h3F1JHrIzZFvcF3SpfsLGCT6Oq7jtnbw_3r_Klcvjwu5nfL0kkQfUnBeimDMsJLtGA5TrnT3oEiZ4MO5I1E4QEVGmcxEEcv9Yxn1EqtZnLMbo6-Oc_HQKmv1u0Qt3llJbSwfMqFsJkFR5aLbUqRQtXFnDPuK-DV4WXVn5dlzeSoSfmeX9f_BV-Jp2y9</recordid><startdate>202204</startdate><enddate>202204</enddate><creator>Yu, Haijun</creator><creator>Li, Shengyang</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>E3H</scope><scope>F2A</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-2472-6354</orcidid></search><sort><creationdate>202204</creationdate><title>Improved interactive color visualization approach for hyperspectral images</title><author>Yu, Haijun ; Li, Shengyang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c312t-ef8d33f472d3a8180a50c6dc14ec8f6fed73a2d1a4a7c8afe0ad3690ec8836493</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Color</topic><topic>Hyperspectral imaging</topic><topic>Interactive control</topic><topic>Multilayers</topic><topic>Real time</topic><topic>Remote sensing</topic><topic>Visualization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Haijun</creatorcontrib><creatorcontrib>Li, Shengyang</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>Library & Information Sciences Abstracts (LISA)</collection><collection>Library & Information Science Abstracts (LISA)</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Information visualization</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Haijun</au><au>Li, Shengyang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Improved interactive color visualization approach for hyperspectral images</atitle><jtitle>Information visualization</jtitle><date>2022-04</date><risdate>2022</risdate><volume>21</volume><issue>2</issue><spage>153</spage><epage>165</epage><pages>153-165</pages><issn>1473-8716</issn><eissn>1473-8724</eissn><abstract>Hyperspectral images (HSIs) have become increasingly prominent as they can maintain the subtle spectral differences of the imaged objects. Designing approaches and tools for analyzing HSIs presents a unique set of challenges due to their high-dimensional characteristics. An improved color visualization approach is proposed in this article to achieve communication between users and HSIs in the field of remote sensing. Under the real-time interactive control and color visualization, this approach can help users intuitively obtain the rich information hidden in original HSIs. Using the dimensionality reduction (DR) method based on band selection, high-dimensional HSIs are reduced to low-dimensional images. Through drop-down boxes, users can freely specify images that participate in the combination of RGB channels of the output image. Users can then interactively and independently set the fusion coefficient of each image within an interface based on concentric circles. At the same time, the output image will be calculated and visualized in real time, and the information it reflects will also be different. 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subjects | Color Hyperspectral imaging Interactive control Multilayers Real time Remote sensing Visualization |
title | Improved interactive color visualization approach for hyperspectral images |
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