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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.