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  2. Kernel (image processing) - Wikipedia

    en.wikipedia.org/wiki/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.

  3. Normalization (image processing) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(image...

    max is the maximum value for color level in the input image within the selected kernel. min is the minimum value for color level in the input image within the selected kernel. [4] Local contrast stretching considers each range of color palate in the image (R, G, and B) separately, providing a set of minimum and maximum values for each color palate.

  4. Difference of Gaussians - Wikipedia

    en.wikipedia.org/wiki/Difference_of_Gaussians

    When utilized for image enhancement, the difference of Gaussians algorithm is typically applied when the size ratio of kernel (2) to kernel (1) is 4:1 or 5:1. In the example images, the sizes of the Gaussian kernels employed to smooth the sample image were 10 pixels and 5 pixels.

  5. Gaussian blur - Wikipedia

    en.wikipedia.org/wiki/Gaussian_blur

    It is a widely used effect in graphics software, typically to reduce image noise and reduce detail. The visual effect of this blurring technique is a smooth blur resembling that of viewing the image through a translucent screen, distinctly different from the bokeh effect produced by an out-of-focus lens or the shadow of an object under usual ...

  6. 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. This weight can be based on a Gaussian distribution.

  7. Video super-resolution - Wikipedia

    en.wikipedia.org/wiki/Video_super-resolution

    Blur kernel, downscaling operation and additive noise should be estimated for given input to achieve better results. Video super-resolution approaches tend to have more components than the image counterparts as they need to exploit the additional temporal dimension.

  8. Fisher kernel - Wikipedia

    en.wikipedia.org/wiki/Fisher_kernel

    The Fisher kernel can result in a compact and dense representation, which is more desirable for image classification [4] and retrieval [5] [6] problems. The Fisher Vector (FV), a special, approximate, and improved case of the general Fisher kernel, [7] is an image representation obtained by pooling local image features. The FV encoding stores ...

  9. Kernel - Wikipedia

    en.wikipedia.org/wiki/Kernel

    Kernel (linear algebra) or null space, a set of vectors mapped to the zero vector; Kernel (category theory), a generalization of the kernel of a homomorphism; Kernel (set theory), an equivalence relation: partition by image under a function; Difference kernel, a binary equalizer: the kernel of the difference of two functions