This paper explores the feasibility of using hyperspectral imagery for blueberry fruit detection. Some bands of hyperspectral images offer redundant information. A Kullback-Leibler divergence (KLD) based band selection method is used to select the most useful bands. Forty hyperspectral images of blueberry plants were taken from the field with 1-millimeter special resolution. The proposed KLD based band selection method took advantage of the high spatial resolution of the blueberry hyperspectral images. The performance of the selected bands was compared with an unsupervised band selection strategy. The selected bands may be used for developing a blueberry detection system with a multi-spectral camera, which is of much lower cost than a hyperspectral camera.
|Original language||English (US)|
|Title of host publication||2013 5th Workshop on Hyperspectral Image and Signal Processing|
|Subtitle of host publication||Evolution in Remote Sensing, WHISPERS 2013|
|Publisher||IEEE Computer Society|
|State||Published - Jun 28 2013|
|Event||5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2013 - Gainesville, United States|
Duration: Jun 26 2013 → Jun 28 2013
|Name||Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing|
|Other||5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2013|
|Period||6/26/13 → 6/28/13|
Bibliographical notePublisher Copyright:
© 2013 IEEE.
Copyright 2019 Elsevier B.V., All rights reserved.
- Band selection
- Blueberry detection
- Hyperspectral imagery
- Kullback-Leibler divergence