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  2. Gaussian blur - Wikipedia

    en.wikipedia.org/wiki/Gaussian_blur

    The difference between a small and large Gaussian blur. In image processing, a Gaussian blur (also known as Gaussian smoothing) is the result of blurring an image by a Gaussian function (named after mathematician and scientist Carl Friedrich Gauss). It is a widely used effect in graphics software, typically to reduce image noise and

  3. 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.

  4. Boris Continuum Complete - Wikipedia

    en.wikipedia.org/wiki/Boris_Continuum_Complete

    Boris Continuum Complete is a special effects plug-in package that works in conjunction with Adobe Creative Suite, including CS6, Avid editing and finishing systems such as Sony Vegas Pro, and Apple Final Cut Pro.

  5. Miniature faking - Wikipedia

    en.wikipedia.org/wiki/Miniature_faking

    A miniature can also be simulated digitally, using an image editor to blur the top and bottom of the photograph, so that only the subject is sharp. With basic techniques, e.g., a tool such as Adobe Photoshop 's Lens Blur filter, [ 9 ] using sharpness gradients extending from the middle of the image to the top and bottom, the effect is quite ...

  6. ImageMagick - Wikipedia

    en.wikipedia.org/wiki/ImageMagick

    Draw: add shapes or text to an image. Decorate: add a border or frame to an image. Special effects: blur, sharpen, threshold, or tint an image. Animation: assemble a GIF animation file from a sequence of images. Text and comments: insert descriptive or artistic text in an image. Image identification: describe the format and attributes of an image.

  7. Unsharp masking - Wikipedia

    en.wikipedia.org/wiki/Unsharp_masking

    The software applies a Gaussian blur to a copy of the original image and then compares it to the original. If the difference is greater than a user-specified threshold setting, the images are (in effect) subtracted. Digital unsharp masking is a flexible and powerful way to increase sharpness, especially in scanned images.

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