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  2. Image gradient - Wikipedia

    en.wikipedia.org/wiki/Image_gradient

    Light areas indicate higher pixel values A blue and green color gradient. An image gradient is a directional change in the intensity or color in an image. The gradient of the image is one of the fundamental building blocks in image processing. For example, the Canny edge detector uses image gradient for edge detection.

  3. OpenCV - Wikipedia

    en.wikipedia.org/wiki/OpenCV

    The first alpha version of OpenCV was released to the public at the IEEE Conference on Computer Vision and Pattern Recognition in 2000, and five betas were released between 2001 and 2005. The first 1.0 version was released in 2006. A version 1.1 "pre-release" was released in October 2008. The second major release of the OpenCV was in October 2009.

  4. Guided filter - Wikipedia

    en.wikipedia.org/wiki/Guided_filter

    When the guidance image is the same as the filtering input .The guided filter removes noise in the input image while preserving clear edges. Specifically, a “flat patch” or a “high variance patch” can be specified by the parameter of the guided filter.

  5. Gradient-domain image processing - Wikipedia

    en.wikipedia.org/wiki/Gradient-domain_image...

    The gradient is obtained from an existing image and modified for image editing purposes. Various operators, such as finite difference or Sobel, can be used to find the gradient of a given image. This gradient can then be manipulated directly to produce several different effects when the resulting image is solved for.

  6. Gradient vector flow - Wikipedia

    en.wikipedia.org/wiki/Gradient_Vector_Flow

    Gradient vector flow (GVF), a computer vision framework introduced by Chenyang Xu and Jerry L. Prince, [1] [2] is the vector field that is produced by a process that smooths and diffuses an input vector field. It is usually used to create a vector field from images that points to object edges from a distance.

  7. Prewitt operator - Wikipedia

    en.wikipedia.org/wiki/Prewitt_operator

    At each point in the image, the result of the Prewitt operator is either the corresponding gradient vector or the norm of this vector. The Prewitt operator is based on convolving the image with a small, separable, and integer valued filter in horizontal and vertical directions and is therefore relatively inexpensive in terms of computations ...

  8. Comparison gallery of image scaling algorithms - Wikipedia

    en.wikipedia.org/wiki/Comparison_gallery_of...

    Simple Fourier based interpolation based on padding of the frequency domain with zero components (a smooth-window-based approach would reduce the ringing).Beside the good conservation of details, notable is the ringing and the circular bleeding of content from the left border to right border (and way around).

  9. Bilateral filter - Wikipedia

    en.wikipedia.org/wiki/Bilateral_filter

    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.