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image-processing

Grayscale images as a matrix of intensities

taught

One number per pixel, 0 (black) to 255 (white) at 8-bit depth, and nothing else.

Taught in

Requires

Required by

Local knowledge map

Local knowledge map

Alpha channels and compositing Binary images and structuring elements Brightness adjustment and the image negative Choosing a smoothing filter for a noise type Contrast stretching and clipping Gamma/power-law transformations and display nonlinearity Histogram equalization Integer vs. floating-point image representations Log transformations Neighborhood operations and the sliding window Quantization RGB and device color The channel axis, RGBA shape, and the ellipsis shortcut Thresholding as a point operation Binary images and image metadata Bit depth and dynamic range Noise models: Gaussian, salt-and-pepper,… Point operations RGB and multichannel images The image histogram Grayscale images as a matrix of intensities Spatial resolution and pixel density Translation and scaling Pixels and image dimensions An image as a matrix-valued function of pixel coordinates

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Solid arrows are required prerequisites; dashed are recommended or helpful. Lower rows are more foundational. Click any box to jump to that concept.