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  2. Taxicab geometry - Wikipedia

    en.wikipedia.org/wiki/Taxicab_geometry

    Taxicab geometry or Manhattan geometry is geometry where the familiar Euclidean distance is ignored, and the distance between two points is instead defined to be the sum of the absolute differences of their respective Cartesian coordinates, a distance function (or metric) called the taxicab distance, Manhattan distance, or city block distance.

  3. Sum of absolute differences - Wikipedia

    en.wikipedia.org/wiki/Sum_of_absolute_differences

    There are exactly three unique locations within the search image where the template may fit: the left side of the image, the center of the image, and the right side of the image. To calculate the SAD values, the absolute value of the difference between each corresponding pair of pixels is used: the difference between 2 and 2 is 0, 4 and 1 is 3 ...

  4. Distance transform - Wikipedia

    en.wikipedia.org/wiki/Distance_transform

    A distance transform, also known as distance map or distance field, is a derived representation of a digital image.The choice of the term depends on the point of view on the object in question: whether the initial image is transformed into another representation, or it is simply endowed with an additional map or field.

  5. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    An image distance measure compares the similarity of two images in various dimensions such as color, texture, shape, and others. For example, a distance of 0 signifies an exact match with the query, with respect to the dimensions that were considered. As one may intuitively gather, a value greater than 0 indicates various degrees of ...

  6. City block - Wikipedia

    en.wikipedia.org/wiki/City_block

    A city block, residential block, urban block, or simply block is a central element of urban planning and urban design. In a city with a grid system, the block is the smallest group of buildings that is surrounded by streets. City blocks are the space for buildings within the street pattern of a city, and form the basic unit of a city's urban ...

  7. Neighborhood operation - Wikipedia

    en.wikipedia.org/wiki/Neighborhood_operation

    In computer vision and image processing a neighborhood operation is a commonly used class of computations on image data which implies that it is processed according to the following pseudo code: Visit each point p in the image data and do { N = a neighborhood or region of the image data around the point p result(p) = f(N) }

  8. Comparison gallery of image scaling algorithms - Wikipedia

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

    The resulting image is larger than the original, and preserves all the original detail, but has (possibly undesirable) jaggedness. The diagonal lines of the "W", for example, now show the "stairway" shape characteristic of nearest-neighbor interpolation. Other scaling methods below are better at preserving smooth contours in the image.

  9. Fréchet inception distance - Wikipedia

    en.wikipedia.org/wiki/Fréchet_inception_distance

    The distance between the two distributions is calculated as the earth mover's distance or the Wasserstein distance between the two Gaussian distributions. Rather than directly comparing images pixel by pixel (for example, as done by the L2 norm ), the FID compares the mean and standard deviation of the deepest layer in Inception v3 (the 2048 ...