Image processing broadly refers to the manipulation or analysis of images using algorithms. It is a field at the intersection of signal processing and computer vision. Classic image processing tasks include enhancement (contrast stretching, histogram equalization), filtering (blurring, sharpening, edge detection), geometric transformations (rotation, scaling, warping), noise reduction (denoising), compression, and color space conversions. It often involves pixel-wise operations or small neighborhood operations (using convolution masks). Unlike high-level computer vision, which tries to infer semantic information (like “there’s a cat”), image processing might be more about improving the image or extracting low-level features (like detecting edges or corners). Many image processing algorithms are deterministic and well-defined (like Canny for edges or median filter for noise removal). It’s foundational for preparing images for analysis or for improving visual quality.
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