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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.
Red Blue Blur, or The Blur, an alternate identity for Clark Kent in Smallville The Atlanta Blur or The Blur, a character in the Marvel MAX comic Supreme Power Blurr (Transformers) , Transformers fictional robot superheroes
The difference between a small and large Gaussian blur. In image processing, a Gaussian blur (also known as Gaussian smoothing) is the result of blurring an image by a Gaussian function (named after mathematician and scientist Carl Friedrich Gauss). It is a widely used effect in graphics software, typically to reduce image noise and reduce detail.
From left to right: an original photo with no bokeh or blur; the same photo with synthetic bokeh effect applied to its background; the same photo with Gaussian blur applied to its background. Bokeh can be simulated by convolving the image with a kernel that corresponds to the image of an out-of-focus point source taken with a real camera.
Display motion blur, also called HDTV blur and LCD motion blur, refers to several visual artifacts (anomalies or unintended effects affecting still or moving images) that are frequently found on modern consumer high-definition television sets and flat-panel displays for computers.
Modern trends toward just-in-time compilation and bytecode interpretation at times blur the traditional categorizations of compilers and interpreters even further. Some language specifications spell out that implementations must include a compilation facility; for example, Common Lisp .
Left: original image. Right: image processed with bilateral filter. A bilateral filter is a non-linear, edge-preserving, and noise-reducing smoothing filter for images.It replaces the intensity of each pixel with a weighted average of intensity values from nearby pixels.
Bootstrap aggregating, also called bagging (from bootstrap aggregating) or bootstrapping, is a machine learning (ML) ensemble meta-algorithm designed to improve the stability and accuracy of ML classification and regression algorithms.