Abstract
The data recorded by current algorithms contains more errors, which reduces the quality of hyperspectral remote sensing images and affects the fusion results. A fusion algorithm based on improved IHS transform is proposed. In order to avoid the noise and diffusion spread and the uniform distribution of gray level, the detail information is preserved and the image is geometric corrected, denoised and histogram equalized. Then the feature extraction, edge detection and feature matching are performed to the images. The weighted average fusion criterion is used to improve the fusion algorithm of IHS transform to improve the spectral distortion of fusion images. Through statistical and visual interpretation of evaluation results, the proposed fusion algorithm preserves the original spectral information and has good visual effects, which is more in line with human subjective evaluation criteria.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
Cited by
5 articles.
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