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  2. 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.

  3. 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.

  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. scikit-image - Wikipedia

    en.wikipedia.org/wiki/Scikit-image

    scikit-image (formerly scikits.image) is an open-source image processing library for the Python programming language. [2] It includes algorithms for segmentation , geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection , and more. [ 3 ]

  6. Image scaling - Wikipedia

    en.wikipedia.org/wiki/Image_scaling

    Image scaling can be interpreted as a form of image resampling or image reconstruction from the view of the Nyquist sampling theorem.According to the theorem, downsampling to a smaller image from a higher-resolution original can only be carried out after applying a suitable 2D anti-aliasing filter to prevent aliasing artifacts.

  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. Sum of absolute differences - Wikipedia

    en.wikipedia.org/wiki/Sum_of_absolute_differences

    These differences are summed to create a simple metric of block similarity, the L 1 norm of the difference image or Manhattan distance between two image blocks. The sum of absolute differences may be used for a variety of purposes, such as object recognition , the generation of disparity maps for stereo images, and motion estimation for video ...

  9. Ridge detection - Wikipedia

    en.wikipedia.org/wiki/Ridge_detection

    Ridges of this image, once projected to the original image, were to be analogous to a shape skeleton (e.g., the Blum medial axis) of the original image. What follows is a definition for the maximal scale ridge of a function of three variables, one of which is a "scale" parameter.