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  2. Noiseware - Wikipedia

    en.wikipedia.org/wiki/Noiseware

    Noiseware is a image noise reduction software by Imagenomic, available for Adobe Photoshop, Photoshop Elements, Apple Aperture, Microsoft Windows (stand-alone) and iOS. [1] In addition to the paid Noiseware 5, an older version (2.6) is available as a free-to-use "Community Edition".

  3. Neat Image - Wikipedia

    en.wikipedia.org/wiki/Neat_Image

    Neat Image is an image noise reduction software by ABSoft. It is available for Windows (stand alone, or Photoshop plugin), Mac OS X (stand alone or Aperture or Photoshop plugin) and Linux (stand alone).

  4. Noise Ninja - Wikipedia

    en.wikipedia.org/wiki/Noise_Ninja

    Noise Ninja is a proprietary noise reduction application and Photoshop plugin which attempts to eliminate noise present in photos taken with a digital camera. It uses custom profiles for each camera to increase the effectiveness of the noise reduction algorithms used. [1] Noise Ninja's development was discontinued when Photo Ninja was introduced.

  5. Median filter - Wikipedia

    en.wikipedia.org/wiki/Median_filter

    Example of 3 median filters of varying radiuses applied to the same noisy photograph. The median filter is a non-linear digital filtering technique, often used to remove noise from an image, [1] signal, [2] and video. [3]

  6. Blend modes - Wikipedia

    en.wikipedia.org/wiki/Blend_modes

    Adobe Photoshop generates a pseudo-random noise dither pattern on startup, with each pixel location in a 2D raster array assigned a gray value (R=G=B) and an alpha value of 1 ("on"). As the opacity of the top layer is reduced, the alpha value of some of the gray pixels is switched from 1 to 0 ("off"), with the result that image pixels ...

  7. Bilateral filter - Wikipedia

    en.wikipedia.org/wiki/Bilateral_filter

    Left: original image. Right: image processed with bilateral filter. A bilateral filter is a non-linear, edge-preserving, and noise-reducing smoothing filter for images.It replaces the intensity of each pixel with a weighted average of intensity values from nearby pixels.

  8. Gaussian blur - Wikipedia

    en.wikipedia.org/wiki/Gaussian_blur

    Most edge-detection algorithms are sensitive to noise; the 2-D Laplacian filter, built from a discretization of the Laplace operator, is highly sensitive to noisy environments. Using a Gaussian Blur filter before edge detection aims to reduce the level of noise in the image, which improves the result of the following edge-detection algorithm.

  9. Image editing - Wikipedia

    en.wikipedia.org/wiki/Image_editing

    Excessive noise reduction leads to a loss of detail, and its application is hence subject to a trade-off between the undesirability of the noise itself and that of the reduction artifacts. Noise tends to invade images when pictures are taken in low light settings. A new picture can be given an 'antiqued' effect by adding uniform monochrome noise.