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Image restoration can be broadly categorized into two main types: spatial domain and frequency domain methods. Spatial domain techniques operate directly on the image pixels, while frequency domain methods transform the image into the frequency domain using techniques such as the Fourier transform, where restoration operations are performed.
Background image (left) and foreground image. All detection techniques are based on modelling the background of the image, i.e. set the background and detect which changes occur. Defining the background can be very difficult when it contains shapes, shadows, and moving objects.
Pixelization (in British English pixelisation) or mosaic processing is any technique used in editing images or video, whereby an image is blurred by displaying part or all of it at a markedly lower resolution. It is primarily used for censorship. The effect is a standard graphics filter, available in all but the most basic bitmap graphics editors.
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.
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.
Censor bars are typically used for satire, [3] [4] although they remain in contemporary use to address privacy concerns. Censor bars are also used in art forms such as blackout poetry . Censor bars may also have the words 'censored', 'redacted', 'private information', 'sensitive information', etc. to indicate their presence.