원문정보
초록
영어
The goal of pan-sharpening is to increase both spatial and spectral resolution of multispectral images. Intensity-hue-saturation (IHS) is one of widely efficient image fusion methods used in recent years. The drawback of IHS is spectral distortion in its results which can be improved by use of wavelet decomposition in IHS-based pan-sharpening methods. Employing Wavelet transforms enhances the resolution of Multispectral (MS) images while maintaining the spectral properties. This paper presents an adaptive IHS-based fusion using "à trous" wavelet (ATW) decomposition based on injecting weighted high frequency components of high spatial panchromatic (PAN) image obtained through à trous decomposition into resampled version of the MS images. Furthermore, the parameters used in the proposed algorithm are optimized through the genetic and Teaching-Learning algorithms. Finally, the proposed method is evaluated using the IKONOS and Landsat ETM+ images and compared to the other conventional methods to confirm its superiority.
목차
1. Introduction
2. Overview of Some Pan-sharpening Methods
2.1. IHS Fusion based Method
2.2. Generalized IHS
2.3. PCA
2.4. Multi-resolution Analysis based Image Fusion Methods
2.5. Generalized Laplacian Pyramid with Spectral Distortion Minimization(GLP-SDM)
3. Optimization Methodology
3.1. Basic Concept of Genetic Algorithm
3.2. Using GA for Pan-sharpening
3.3. Basic Concept of Teaching-Learning Algorithm
3.4. Steps of TLBO
4. Improved Adaptive IHS-ATW Merger
5. Case Studies
5.1. Spectral and Spatial Quality Indicators
5.2. Case 1: IKONOS Dataset Simulation Results
5.3. Case 2: Landsat ETM+ Dataset Simulation Results
6. Conclusion
References