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  2. Comparison gallery of image scaling algorithms - Wikipedia

    en.wikipedia.org/wiki/Comparison_gallery_of...

    Scalable Vector Graphics are well suited to simple geometric images, while photographs do not fare well with vectorization due to their complexity. Note that the special characteristics of vectors allow for greater resolution example images. The other algorithms are standardized to a resolution of 160x160 and 218x80 pixels respectively.

  3. Otsu's method - Wikipedia

    en.wikipedia.org/wiki/Otsu's_method

    The criterion is that, when the difference between Otsu’s thresholds computed from two consecutive iterations is less than a small number, the iteration shall stop. For the last iteration, pixels above η n {\displaystyle \eta _{n}} are assigned to the foreground class and pixels below the threshold are assigned to the background class.

  4. Image subtraction - Wikipedia

    en.wikipedia.org/wiki/Image_subtraction

    For this technique to work, the two images must first be spatially aligned to match features between them, and their photometric values and point spread functions must be made compatible, either by careful calibration, or by post-processing (using color mapping). The complexity of the pre-processing needed before differencing varies with the ...

  5. Wiener deconvolution - Wikipedia

    en.wikipedia.org/wiki/Wiener_deconvolution

    From left: Original image, blurred image, image deblurred using Wiener deconvolution. In mathematics, Wiener deconvolution is an application of the Wiener filter to the noise problems inherent in deconvolution. It works in the frequency domain, attempting to minimize the impact of deconvolved noise at frequencies which have a poor signal-to ...

  6. 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.

  7. Difference of Gaussians - Wikipedia

    en.wikipedia.org/wiki/Difference_of_Gaussians

    When utilized for image enhancement, the difference of Gaussians algorithm is typically applied when the size ratio of kernel (2) to kernel (1) is 4:1 or 5:1. In the example images, the sizes of the Gaussian kernels employed to smooth the sample image were 10 pixels and 5 pixels.

  8. Scale-invariant feature transform - Wikipedia

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

    The convolved images are grouped by octave (an octave corresponds to doubling the value of ), and the value of is selected so that we obtain a fixed number of convolved images per octave. Then the Difference-of-Gaussian images are taken from adjacent Gaussian-blurred images per octave.

  9. Phase correlation - Wikipedia

    en.wikipedia.org/wiki/Phase_correlation

    Phase correlation is an approach to estimate the relative translative offset between two similar images (digital image correlation) or other data sets.It is commonly used in image registration and relies on a frequency-domain representation of the data, usually calculated by fast Fourier transforms.