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Kernel (image processing) 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. Or more simply, when each pixel in the output image is a function of the nearby pixels (including ...
Digital image processing. Digital image processing is the use of a digital computer to process digital images through an algorithm. [1][2] As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data ...
Histogram equalization accomplishes this by effectively spreading out the highly populated intensity values which are used to degrade image contrast. The method is useful in images with backgrounds and foregrounds that are both bright or both dark. In particular, the method can lead to better views of bone structure in x-ray images, and to ...
Gabor filter. In image processing, a Gabor filter, named after Dennis Gabor, who first proposed it as a 1D filter. [1] The Gabor filter was first generalized to 2D by Gösta Granlund, [2] by adding a reference direction. The Gabor filter is a linear filter used for texture analysis, which essentially means that it analyzes whether there is any ...
In digital image processing convolutional filtering plays an important role in many important algorithms in edge detection and related processes (see Kernel (image processing)) In optics, an out-of-focus photograph is a convolution of the sharp image with a lens function. The photographic term for this is bokeh. In image processing applications ...
The Sobel operator, sometimes called the Sobel–Feldman operator or Sobel filter, is used in image processing and computer vision, particularly within edge detection algorithms where it creates an image emphasising edges. It is named after Irwin Sobel and Gary M. Feldman, colleagues at the Stanford Artificial Intelligence Laboratory (SAIL).
Gradient domain image processing, also called Poisson image editing, [1] is a type of digital image processing that operates directly on the differences between neighboring pixels, rather than on the pixel values. Mathematically, an image gradient represents the derivative of an image, so the goal of gradient domain processing is to construct a ...
In digital image processing, the sum of absolute differences (SAD) is a measure of the similarity between image blocks. It is calculated by taking the absolute difference between each pixel in the original block and the corresponding pixel in the block being used for comparison. These differences are summed to create a simple metric of block ...
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