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  2. Category:Image noise reduction techniques - Wikipedia

    en.wikipedia.org/wiki/Category:Image_noise...

    This category collects Wikipedia articles on techniques for removal or reduction of noise and artifacts from images and multi-dimensional data. Pages in category "Image noise reduction techniques" The following 19 pages are in this category, out of 19 total.

  3. 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.

  4. Image noise - Wikipedia

    en.wikipedia.org/wiki/Image_noise

    The high sensitivity image quality of a given camera (or RAW development workflow) may depend greatly on the quality of the algorithm used for noise reduction. Since noise levels increase as ISO sensitivity is increased, most camera manufacturers increase the noise reduction aggressiveness automatically at higher sensitivities.

  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, [1] signal, [2] and video. [3] Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge detection on an image).

  6. Block-matching and 3D filtering - Wikipedia

    en.wikipedia.org/wiki/Block-matching_and_3D...

    Block-matching and 3D filtering (BM3D) is a 3-D block-matching algorithm used primarily for noise reduction in images. [1] It is one of the expansions of the non-local means methodology. [ 2 ] There are two cascades in BM3D: a hard-thresholding and a Wiener filter stage, both involving the following parts: grouping, collaborative filtering ...

  7. 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.

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