文章基本信息

标题：Improved IHS Pan-Sharpening Method Based on Adaptive Injection of À trous Wavelet Decomposition
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作者：Saber Noroozpour Lari ; Mehran Yazdi
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：3
页码：291-308
DOI：10.14257/ijsip.2016.9.3.26
出版社：SERSC
摘要：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.
关键词：à trous wavelet; genetic algorithm; image fusion; intensity-hue-saturation; ; pan-sharpening