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  2. Normalization (image processing) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(image...

    A Contrast Stretching Transformation can be achieved by: Contrast Stretching Transformation Graph reference for derivation. 1. Stretching the dark range of input values into a wider range of output values: This involves increasing the brightness of the darker areas in the image to enhance details and improve visibility. 2.

  3. Histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Histogram_equalization

    The goal of these methods, especially MBOBHE, is to improve the contrast without producing brightness mean-shift and detail loss artifacts by modifying the HE algorithm. [ 1 ] A signal transform equivalent to histogram equalization also seems to happen in biological neural networks so as to maximize the output firing rate of the neuron as a ...

  4. Adaptive histogram equalization - Wikipedia

    en.wikipedia.org/wiki/Adaptive_histogram...

    Adaptive histogram equalization (AHE) is a computer image processing technique used to improve contrast in images. It differs from ordinary histogram equalization in the respect that the adaptive method computes several histograms, each corresponding to a distinct section of the image, and uses them to redistribute the lightness values of the image.

  5. Gamma correction - Wikipedia

    en.wikipedia.org/wiki/Gamma_correction

    For a CRT, the gamma that relates brightness to voltage is usually in the range 2.35 to 2.55; video look-up tables in computers usually adjust the system gamma to the range 1.8 to 2.2, [1] which is in the region that makes a uniform encoding difference give approximately uniform perceptual brightness difference, as illustrated in the diagram at ...

  6. Image restoration by artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Image_restoration_by...

    Image enhancement techniques (like contrast stretching or de-blurring by a nearest neighbor procedure) provided by imaging packages use no a priori model of the process that created the image. With image enhancement noise can effectively be removed by sacrificing some resolution, but this is not acceptable in many applications.

  7. Scale-invariant feature transform - Wikipedia

    en.wikipedia.org/wiki/Scale-invariant_feature...

    In contrast to the classic SIFT approach, Wagner et al. use the FAST corner detector for feature detection. The algorithm also distinguishes between the off-line preparation phase where features are created at different scale levels and the on-line phase where features are only created at the current fixed scale level of the phone's camera image.

  8. Gaussian blur - Wikipedia

    en.wikipedia.org/wiki/Gaussian_blur

    By contrast, convolving by a circle (i.e., a circular box blur) would more accurately reproduce the bokeh effect. Since the Fourier transform of a Gaussian is another Gaussian, applying a Gaussian blur has the effect of reducing the image's high-frequency components; a Gaussian blur is thus a low-pass filter.

  9. Bundle adjustment - Wikipedia

    en.wikipedia.org/wiki/Bundle_adjustment

    A sparse matrix obtained when solving a modestly sized bundle adjustment problem. This is the arrowhead sparsity pattern of a 992×992 normal-equation (i.e. approximate Hessian) matrix.