03707nam a22005895i 4500 978-3-031-42667-4 DE-He213 20251030110820.0 cr nn 008mamaa 231004s2024 sz | s |||| 0|eng d 9783031426674 978-3-031-42667-4 10.1007/978-3-031-42667-4 doi TK5102.9 TJF bicssc UYS bicssc TEC067000 bisacsh TJF thema UYS thema Paul, Arati. author. aut http://id.loc.gov/vocabulary/relators/aut 66421 Dimensionality Reduction of Hyperspectral Imagery [electronic resource] / by Arati Paul, Nabendu Chaki. 1st ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. XVIII, 116 p. 53 illus., 29 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Introduction -- Remote sensing -- Digital image processing -- Hyperspectral image characteristics -- Dimensionality reduction -- Dataset description -- Pooling based band extraction -- Ranking based band selection -- Band optimization -- Data Driven approach -- Conclusion. This book provides information about different types of dimensionality reduction (DR) methods and their effectiveness in hyperspectral data processing. The authors first explain how hyperspectral imagery (HSI) plays an important role in remote sensing due to its high spectral resolution that enables better identification of different materials on the earth’s surface. The authors go on to describe potential challenges due to HSI being acquired in hundreds of narrow and contiguous bands, represented as a 3-dimensional image cube, often causing the bands to contain information redundancy. They then show how processing a large number of bands adds challenges in terms of computation complexity that reduces efficiency. The authors then present how DR is an essential step in hyperspectral data analysis to solve these issues. Overall, the book helps readers understand the DR processes and its impact in effective HSI analysis. Presents a data driven approach for dimensionality reduction (DR); Discusses the effect of spatial dimension and noise in the context of DR of hyperspectral imagery (HSI); Includes an optimization based approach for DR challenges and identification of gap areas in existing algorithms along with suitable solutions. Signal processing. Image processing Digital techniques. 64228 Computer vision. Computational intelligence. 64052 Geographic information systems. 61967 Signal, Speech and Image Processing. Computer Imaging, Vision, Pattern Recognition and Graphics. 65550 Computational Intelligence. 64052 Geographical Information System. 66422 Chaki, Nabendu. author. aut http://id.loc.gov/vocabulary/relators/aut 66423 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031426667 Printed edition: 9783031426681 Printed edition: 9783031426698 https://doi.org/10.1007/978-3-031-42667-4 ZDB-2-ENG ZDB-2-SXE 56369 56369