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  2. Kernel (image processing) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(image_processing)

    2D convolution with an M × N kernel requires M × N multiplications for each sample (pixel). If the kernel is separable, then the computation can be reduced to M + N multiplications. Using separable convolutions can significantly decrease the computation by doing 1D convolution twice instead of one 2D convolution. [2]

  3. Comparison of raster graphics editors - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_raster...

    Free command line software for 2D or 3D image processing and visualization David Tschumperlé October 2008: 3.4.3 [8] 2024-10-11 Free CECILL-2.1 or CECILL-C: GIMP: Free image editor and graphics creator Spencer Kimball, Peter Mattis: January 1996: 2.10.38 [9] 2024-05-05 Free GPL-3.0-or-later: GimPhoto

  4. Comparison gallery of image scaling algorithms - Wikipedia

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

    Examples of algorithms for this task include New Edge-Directed Interpolation (NEDI), [1] [2] Edge-Guided Image Interpolation (EGGI), [3] Iterative Curvature-Based Interpolation (ICBI), [citation needed] and Directional Cubic Convolution Interpolation (DCCI). [4] A study found that DCCI had the best scores in PSNR and SSIM on a series of test ...

  5. Image editing - Wikipedia

    en.wikipedia.org/wiki/Image_editing

    Image editing encompasses the processes of altering images, whether they are digital photographs, traditional photo-chemical photographs, or illustrations. Traditional analog image editing is known as photo retouching , using tools such as an airbrush to modify photographs or edit illustrations with any traditional art medium .

  6. Separable filter - Wikipedia

    en.wikipedia.org/wiki/Separable_filter

    A separable filter in image processing can be written as product of two more simple filters. Typically a 2-dimensional convolution operation is separated into two 1-dimensional filters.

  7. Image derivative - Wikipedia

    en.wikipedia.org/wiki/Image_derivative

    Image derivatives can be computed by using small convolution filters of size 2 × 2 or 3 × 3, such as the Laplacian, Sobel, Roberts and Prewitt operators. [1] However, a larger mask will generally give a better approximation of the derivative and examples of such filters are Gaussian derivatives [ 2 ] and Gabor filters . [ 3 ]

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