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In image processing, a kernel, convolution matrix, or mask is a small matrix used for blurring, sharpening, embossing, edge detection, and more.This is accomplished by doing a convolution between the kernel and an image.
Computer Vision Annotation Tool (CVAT) is an open source, web-based image and video annotation tool used for labeling data for computer vision algorithms. Originally developed by Intel , CVAT is designed for use by a professional data annotation team, with a user interface optimized for computer vision annotation tasks.
OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]).
Image compression is a type of data compression applied to digital images, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data.
In addition to the eponymous codec library, it packages a suite of auxiliary tools, like the command line encoder cjxl and decoder djxl, the image codec benchmarking tool (speed, quality) benchmark_xl, the image comparison tool of perceptual metric ssimulacra2, as well as the GIMP and gdk-pixbuf plugin file-jxl.
This is the standard blend mode which uses the top layer alone, [3] without mixing its colors with the layer beneath it: [example needed] (,) =where a is the value of a color channel in the underlying layer, and b is that of the corresponding channel of the upper layer.
In GIMP 2.8, the Convert Image to Indexed Colors Option (Image→Mode→Indexed..) allows generation of an optimum palette with a choice in the number of colors from 2 to 256, the option of using a web-optimized palette, using a black and white palette (1 bit) or using a custom palette. It allows unused colors to be removed from the palette and ...
Adaptive histogram equalization (AHE) is a computer image processing technique used to improve contrast in images. It differs from ordinary histogram equalization in the respect that the adaptive method computes several histograms, each corresponding to a distinct section of the image, and uses them to redistribute the lightness values of the image.