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  2. Foreground detection - Wikipedia

    en.wikipedia.org/wiki/Foreground_detection

    Foreground detection is one of the major tasks in the field of computer vision and image processing whose aim is to detect changes in image sequences. Background subtraction is any technique which allows an image's foreground to be extracted for further processing (object recognition etc.). Many applications do not need to know everything about ...

  3. Image editing - Wikipedia

    en.wikipedia.org/wiki/Image_editing

    Basics of image editing. Raster images are stored in a computer in the form of a grid of picture elements, or pixels. These pixels contain the image's color and brightness information. Image editors can change the pixels to enhance the image in many ways. The pixels can be changed as a group, or individually, by the sophisticated algorithms ...

  4. Image noise - Wikipedia

    en.wikipedia.org/wiki/Image_noise

    Image noise is random variation of brightness or color information in images, and is usually an aspect of electronic noise. It can be produced by the image sensor and circuitry of a scanner or digital camera. Image noise can also originate in film grain and in the unavoidable shot noise of an ideal photon detector. Image noise is an undesirable ...

  5. Median filter - Wikipedia

    en.wikipedia.org/wiki/Median_filter

    The median filter is a non-linear digital filtering technique, often used to remove noise from an image or signal. Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge detection on an image).

  6. Noise reduction - Wikipedia

    en.wikipedia.org/wiki/Noise_reduction

    Noise reduction is the process of removing noise from a signal. Noise reduction techniques exist for audio and images. Noise reduction algorithms may distort the signal to some degree. Noise rejection is the ability of a circuit to isolate an undesired signal component from the desired signal component, as with common-mode rejection ratio.

  7. Nyquist–Shannon sampling theorem - Wikipedia

    en.wikipedia.org/wiki/Nyquist–Shannon_sampling...

    Nyquist–Shannon sampling theorem. The Nyquist–Shannon sampling theorem is an essential principle for digital signal processing linking the frequency range of a signal and the sample rate required to avoid a type of distortion called aliasing. The theorem states that the sample rate must be at least twice the bandwidth of the signal to avoid ...

  8. Edge detection - Wikipedia

    en.wikipedia.org/wiki/Edge_detection

    e. Edge detection includes a variety of mathematical methods that aim at identifying edges, defined as curves in a digital image at which the image brightness changes sharply or, more formally, has discontinuities. The same problem of finding discontinuities in one-dimensional signals is known as step detection and the problem of finding signal ...

  9. Image gradient - Wikipedia

    en.wikipedia.org/wiki/Image_gradient

    An image gradient is a directional change in the intensity or color in an image. The gradient of the image is one of the fundamental building blocks in image processing. For example, the Canny edge detector uses image gradient for edge detection. In graphics software for digital image editing, the term gradient or color gradient is also used ...

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