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  2. Edge enhancement - Wikipedia

    en.wikipedia.org/wiki/Edge_enhancement

    Edge enhancement is an image processing filter that enhances the edge contrast of an image or video in an attempt to improve its acutance (apparent sharpness).. The filter works by identifying sharp edge boundaries in the image, such as the edge between a subject and a background of a contrasting color, and increasing the image contrast in the area immediately around the edge.

  3. Comparison gallery of image scaling algorithms - Wikipedia

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

    The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.

  4. Gaussian blur - Wikipedia

    en.wikipedia.org/wiki/Gaussian_blur

    Gaussian blurring is commonly used when reducing the size of an image. When downsampling an image, it is common to apply a low-pass filter to the image prior to resampling. This is to ensure that spurious high-frequency information does not appear in the downsampled image . Gaussian blurs have nice properties, such as having no sharp edges, and ...

  5. 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.This is accomplished by doing a convolution between the kernel and an image.

  6. Median filter - Wikipedia

    en.wikipedia.org/wiki/Median_filter

    Median filtering is one kind of smoothing technique, as is linear Gaussian filtering. All smoothing techniques are effective at removing noise in smooth patches or smooth regions of a signal, but adversely affect edges. Often though, at the same time as reducing the noise in a signal, it is important to preserve the edges.

  7. 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.

  8. Edge detection - Wikipedia

    en.wikipedia.org/wiki/Edge_detection

    Feature enhancement in an image (St Paul's Cathedral, London) using Phase Stretch Transform (PST). Left panel shows the original image and the right panel shows the detected features using PST. The phase stretch transform or PST is a physics-inspired computational approach to signal and image processing. One of its utilities is for feature ...

  9. Edge-preserving smoothing - Wikipedia

    en.wikipedia.org/wiki/Edge-preserving_smoothing

    Edge-preserving filters are designed to automatically limit the smoothing at “edges” in images measured, e.g., by high gradient magnitudes. For example, the motivation for anisotropic diffusion (also called nonuniform or variable conductance diffusion) is that a Gaussian smoothed image is a single time slice of the solution to the heat ...

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