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  2. Gaussian noise - Wikipedia

    en.wikipedia.org/wiki/Gaussian_noise

    Principal sources of Gaussian noise in digital images arise during acquisition e.g. sensor noise caused by poor illumination and/or high temperature, and/or transmission e.g. electronic circuit noise. [3] In digital image processing Gaussian noise can be reduced using a spatial filter, though when smoothing an image, an undesirable outcome may ...

  3. Image noise - Wikipedia

    en.wikipedia.org/wiki/Image_noise

    Image noise can also originate in film grain and in the unavoidable shot noise of an ideal photon detector. Image noise is an undesirable by-product of image capture that obscures the desired information. Typically the term “image noise” is used to refer to noise in 2D images, not 3D images.

  4. Gaussian blur - Wikipedia

    en.wikipedia.org/wiki/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 reduce detail.

  5. Total variation denoising - Wikipedia

    en.wikipedia.org/wiki/Total_variation_denoising

    The regularization parameter plays a critical role in the denoising process. When =, there is no smoothing and the result is the same as minimizing the sum of squares.As , however, the total variation term plays an increasingly strong role, which forces the result to have smaller total variation, at the expense of being less like the input (noisy) signal.

  6. Gaussian filter - Wikipedia

    en.wikipedia.org/wiki/Gaussian_filter

    By averaging pixel values with a weighted Gaussian distribution, the filter effectively blurs the image, diminishing high-frequency noise. [12] Edge Detection: Gaussian filters are often used as a preprocessing step in edge detection algorithms. By smoothing the image, they help to minimize the impact of noise before applying methods like the ...

  7. Non-local means - Wikipedia

    en.wikipedia.org/wiki/Non-local_means

    Application of non-local means to an image corrupted by Gaussian noise Non-local means is an algorithm in image processing for image denoising . Unlike "local mean" filters, which take the mean value of a group of pixels surrounding a target pixel to smooth the image, non-local means filtering takes a mean of all pixels in the image, weighted ...

  8. Noise (signal processing) - Wikipedia

    en.wikipedia.org/wiki/Noise_(signal_processing)

    Electromagnetically induced noise, audible noise due to electromagnetic vibrations in systems involving electromagnetic fields; Noise (video), such as "snow" Noise (radio), such as "static", in radio transmissions; Image noise, affects images, usually digital ones Salt and pepper noise or spike noise, scattered very dark or very light pixels

  9. White noise - Wikipedia

    en.wikipedia.org/wiki/White_noise

    This model is called a Gaussian white noise signal (or process). In the mathematical field known as white noise analysis, a Gaussian white noise is defined as a stochastic tempered distribution, i.e. a random variable with values in the space ′ of tempered distributions.