MATLAB Implementation of Image Fusion Techniques
Comprehensive image fusion approaches including high-pass filtering, IHS transformation, principal component analysis, wavelet-based methods, and combined wavelet-IHS methodology.
Explore MATLAB source code curated for "IHS变换" with clean implementations, documentation, and examples.
Comprehensive image fusion approaches including high-pass filtering, IHS transformation, principal component analysis, wavelet-based methods, and combined wavelet-IHS methodology.
By applying the IHS transformation to RGB components formed from three bands of multispectral images, the spatial features (I) and spectral features (H and S) of the image can be separated. This technique enables independent manipulation of image brightness and color information, which is particularly useful in applications like remote sensing, image fusion, and color enhancement.
A remote sensing image fusion implementation combining discrete wavelet transform and IHS transformation, specifically designed for merging multispectral and panchromatic images with detailed code structure and algorithm workflow.
MATLAB code for performing IHS transformation on images, including several commonly used color image fusion algorithms such as weighted average, wavelet transform, and principal component analysis methods
MATLAB programs for image fusion using IHS transform and hybrid IHS-wavelet frame transform approaches, featuring detailed algorithm explanations and implementation methods
Implementation of multiple techniques for panchromatic and multispectral image fusion: (1) IHS Transform, (2) High-Pass Filtering, (3) GIHS Method, (4) Wavelet Transform, (5) PCA, and (6) Brovey Transform, including algorithm explanations and code implementation insights.
MATLAB Implementation of Image Fusion Algorithms
Multi-Method Panchromatic and Multispectral Image Fusion with Algorithm Implementations
Performing IHS Transformation on Images with Code Implementation Details