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An example of image processing is applying a filter to a photograph to enhance its colors or remove noise. For instance, using a "sharpen" filter to make edges more distinct or a "blur" filter to reduce fine details.

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A image operator ? transform an input f into output image g, i.e. g=?f. The image processing operators can be classified to belong to one the 4 categories: Point Operators. A point operator acts on individual pixels, i.e. g(x)=?(f(x)). A simple example is to add a constant to all pixels in an image.

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The fundamental steps in any typical Digital Image Processing pipeline are as follows: Image Acquisition. ... Image Enhancement. ... Image Restoration. ... Color Image Processing. ... Wavelets and Multi-Resolution Processing. ... Image Compression. ... Morphological Processing. ... Image Segmentation.

Improved image quality: Digital image processing algorithms can improve the visual quality of images, making them clearer, sharper, and more informative. Automated image-based tasks: Digital image processing can automate many image-based tasks, such as object recognition, pattern detection, and measurement.

Actions performed on an image that change the colour content of its pixels usually to detect or bring out some image characteristics.