Paper
18 November 2014 Morphology-based fusion method of hyperspectral image
Song Yue, Zhijie Zhang, Tingting Ren, Chensheng Wang, Hui Yu
Author Affiliations +
Abstract
Hyperspectral image analysis method is widely used in all kinds of application including agriculture identification and forest investigation and atmospheric pollution monitoring. In order to accurately and steadily analyze hyperspectral image, considering the spectrum and spatial information which is provided by hyperspectral data together is necessary. The hyperspectral image has the characteristics of large amount of wave bands and information. Corresponding to the characteristics of hyperspectral image, a fast image fusion method that can fuse the hyperspectral image with high fidelity is studied and proposed in this paper. First of all, hyperspectral image is preprocessed before the morphological close operation. The close operation is used to extract wave band characteristic to reduce dimensionality of hyperspectral image. The spectral data is smoothed at the same time to avoid the discontinuity of the data by combination of spatial information and spectral information. On this basis, Mean-shift method is adopted to register key frames. Finally, the selected key frames by fused into one fusing image by the pyramid fusion method. The experiment results show that this method can fuse hyper spectral image in high quality. The fused image’s attributes is better than the original spectral images comparing to the spectral images and reach the objective of fusion.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Song Yue, Zhijie Zhang, Tingting Ren, Chensheng Wang, and Hui Yu "Morphology-based fusion method of hyperspectral image", Proc. SPIE 9298, International Symposium on Optoelectronic Technology and Application 2014: Imaging Spectroscopy; and Telescopes and Large Optics, 92980B (18 November 2014); https://doi.org/10.1117/12.2070426
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KEYWORDS
Image fusion

Hyperspectral imaging

Image registration

Image quality

Image processing

Feature extraction

Dimension reduction

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