Give an overview of various image fusion techniques.

Image fusion is a process in remote sensing and digital image processing where multiple images, typically from different sensors or at different resolutions, are combined into a single image that retains the best features of the input images. The goal is to provide a more comprehensive and informative representation of the scene being observed. Various techniques are employed for image fusion, each with its strengths and limitations, depending on the application and data types. Here’s an overview of several common image fusion techniques used in remote sensing and digital image processing.

1. Pixel-level Fusion: Pixel-level fusion involves merging images at the individual pixel level. This method is straightforward and directly combines the data from different sources, aiming to preserve spatial and spectral details. Common pixel-level fusion techniques include:

   • Intensity-Hue-Saturation (IHS) Transformation: This technique transforms the image into three components—Intensity, Hue, and Saturation. The high-resolution panchromatic image is used to replace the intensity component, while the hue and saturation components remain unchanged. The inverse transformation reconstructs the fused _________ ______ _____ ________ ______ ___ ________ _________ ___ ____.
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