Image Fusion by Shift Invariant Discrete Wavelet Transform for Remote Sensing Applications

Abd Qubaa
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Abstract

The fusion technique of the spectral bands captured by the sensors carried onboard satellites is one digital processing method for extracting information and detecting ground targets. Image fusion also known as pan-sharpening-provides the necessary means to combine many images into a single composite image that is suitable in visual interpretation processes or in digital interpretation. The principal objective of this study is to find the best suitable algorithms for obtaining integrative information from several separate images in one combined image. Based on the above, a special software system was designed to implement and test the fusion methods used in remote sensing applications by selecting and applying a Shift Invariant Wavelet Transform (SIWT) method to the remote sensing images and then comparing with four other different image fusion algorithms. Two objective mathematical methods were also used to measure the amount of shared information obtained in the images resulting from the fusion, as well as using the visual and Near-Infrared images of the new Sentinel-2 European satellite for a part of Nineveh province as experimental images. The results showed a preference of the wavelet transform method over the other fusion methods for the remote sensing images.
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平移不变离散小波变换在遥感图像融合中的应用
星载传感器捕获的光谱波段融合技术是一种用于提取信息和探测地面目标的数字化处理方法。图像融合,也称为泛锐化,提供了必要的手段,将许多图像组合成一个单一的合成图像,适用于视觉解释过程或数字解释。本研究的主要目的是寻找最合适的算法,从一幅组合图像中获得多幅独立图像的综合信息。在此基础上,设计了一个专门的软件系统,通过对遥感图像选择和应用平移不变小波变换(SIWT)方法,并与其他四种不同的图像融合算法进行比较,实现和测试遥感应用中使用的融合方法。还使用了两种客观的数学方法来测量从融合产生的图像中获得的共享信息的数量,以及使用新的哨兵-2欧洲卫星在尼尼微省部分地区拍摄的视觉和近红外图像作为实验图像。结果表明,小波变换方法对遥感图像的融合优于其他融合方法。
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