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An IHS-Based Pan-Sharpening Method for Spectral Fidelity Improvement Using Ripplet Transform and Compressed Sensing.
Chen Yang1,2, Qingming Zhan3,4,5, Huimin Liu6,7
1School of Urban Design, Wuhan University, 8 Donghu South Road, Wuhan 430072, China. yangchenwhu@whu.edu.cn.
Sensors (Basel, Switzerland)
|October 28, 2018
Summary
This study introduces an improved pan-sharpening technique using ripplet transform and compressed sensing to enhance multi-spectral (MS) images. The novel method effectively boosts spatial resolution while preserving spectral fidelity, outperforming existing approaches.
Area of Science:
- Remote Sensing
- Image Processing
- Computer Vision
Background:
- Pan-sharpening fuses multi-spectral (MS) and panchromatic (PAN) images for enhanced resolution.
- Existing Intensity-Hue-Saturation (IHS) methods often introduce spectral distortion.
Purpose of the Study:
- To develop an advanced IHS-based pan-sharpening method.
- To mitigate spectral distortion in fused images.
- To improve both spatial and spectral resolutions.
Main Methods:
- Applied IHS transform to separate MS image intensity components.
- Utilized discrete ripplet transform (DRT) for multi-scale decomposition.
- Employed compressed sensing for low-frequency component reconstruction.
- Fused high-frequency sub-images using a local variance algorithm.
- Reconstructed the intensity component using local difference-based fusion rules.
Main Results:
- The proposed method demonstrated superior spatial resolution enhancement.
- Achieved improved spectral fidelity compared to state-of-the-art techniques.
- Outperformed Gram-Schmidt (GS) and other leading pan-sharpening methods in quantitative and visual analyses.
- Validated on WorldView-2, Pleiades, and Triplesat datasets.
Conclusions:
- The novel IHS-based method effectively integrates spectral and spatial information.
- Ripplet transform and compressed sensing significantly reduce spectral distortion.
- This approach offers a promising solution for high-quality pan-sharpening in remote sensing applications.
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