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  2. Template:The Mask - Wikipedia

    en.wikipedia.org/wiki/Template:The_Mask

    This template's initial visibility currently defaults to autocollapse, meaning that if there is another collapsible item on the page (a navbox, sidebar, or table with the collapsible attribute), it is hidden apart from its title bar; if not, it is fully visible. To change this template's initial visibility, the |state= parameter may be used:

  3. File:Ballistic mask.svg - Wikipedia

    en.wikipedia.org/wiki/File:Ballistic_mask.svg

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  4. Visual masking - Wikipedia

    en.wikipedia.org/wiki/Visual_masking

    Visual masking involves surrounding a target image (here, the word "radio") with another image. Visual masking is a phenomenon of visual perception. It occurs when the visibility of one image, called a target, is reduced by the presence of another image, called a mask. [1] The target might be invisible or appear to have reduced contrast or ...

  5. Template:Image frame - Wikipedia

    en.wikipedia.org/wiki/Template:Image_frame

    This template creates a frame like those surrounding images. This template can be used to put two or more images into a frame together, or as a wrapper for more complicated templates like Template:Superimpose. Template parameters [Edit template data] Parameter Description Type Status Content content Content of the main section (generally images). Content required Width width The width of the ...

  6. Template:Image label custom/doc - Wikipedia

    en.wikipedia.org/wiki/Template:Image_label...

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  7. Template:Image label marker/doc - Wikipedia

    en.wikipedia.org/wiki/Template:Image_label...

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  8. 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 .

  9. Unsharp masking - Wikipedia

    en.wikipedia.org/wiki/Unsharp_masking

    For image processing, deconvolution is the process of approximately inverting the process that caused an image to be blurred. Specifically, unsharp masking is a simple linear image operation—a convolution by a kernel that is the Dirac delta minus a gaussian blur kernel.