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Image enhancement in remote sensing and digital image processing refers to the process of improving the visual appearance of an image or transforming it into a form better suited for analysis. The main objective is to make certain features more distinguishable and to facilitate interpretation, classification, or extraction of information. Image enhancement techniques can broadly be classified into two categories: spatial domain techniques and frequency domain techniques, each of which has its specific approaches and applications. Spatial domain techniques operate directly on the image pixels and are designed to modify the intensity values of individual pixels or groups of pixels. One of the most basic spatial domain techniques is contrast stretching, which improves the contrast of an image by expanding the range of intensity levels. Linear contrast stretching linearly maps input intensities to output intensities, whereas nonlinear contrast stretching, such as histogram equalization, redistributes pixel intensities to achieve a uniform histogram, enhancing global contrast. Histogram equalization is particularly useful for remote sensing images where certain features may appear in a narrow range of gray levels, making them indistinct. Another important spatial domain approach is image smoothing or filtering, which aims to reduce noise or minor variations in the image. Low-pass filters, such as the averaging filter or Gaussian filter, are used to ________ ____ _________ ______ ___ ______ _________ _____ _________ _________ __________ _______.
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