Hyperspectral image nonlinear abundance estimation method based on constrained least squares
A hyperspectral image, least squares technology, applied in the field of remote sensing image processing, can solve problems such as inaccurate results, and achieve the effects of good adaptability, low computational complexity, good unmixing accuracy and anti-noise performance
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Example Embodiment
[0090] Below, use simulation data and actual remote sensing image data as examples to illustrate the specific implementation of the present invention respectively:
[0091] The nonlinear abundance estimation method (algorithm) based on constrained least squares adopted in the present invention is represented by CNLS-AE.
[0092] 1. Simulation data experiment
[0093] In this section, we test the performance of the proposed algorithm on artificially generated simulation data. We compare the algorithm proposed in this paper with two gradient methods based on GBM and PPNMM, namely GBM-GDA and PPNMM-GDA algorithms mentioned in [7] and [8], respectively. In addition, we also compare with the better performance of the LMM-based FCLS algorithm [10].
[0094] We use Root Mean Square Error (RMSE) and Reconstruction Error (RE) to measure the pros and cons of abundance estimation algorithms. RMSE is used to measure how close the estimated result of the abundance matrix is to the tru...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap