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  2. 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.

  3. 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 ...

  4. Digital image correlation and tracking - Wikipedia

    en.wikipedia.org/wiki/Digital_image_correlation...

    Digital image correlation and tracking is an optical method that employs tracking and image registration techniques for accurate 2D and 3D measurements of changes in images. This method is often used to measure full-field displacement and strains , and it is widely applied in many areas of science and engineering.

  5. Structural similarity index measure - Wikipedia

    en.wikipedia.org/wiki/Structural_similarity...

    The SSIM index is a full reference metric; in other words, the measurement or prediction of image quality is based on an initial uncompressed or distortion-free image as reference. SSIM is a perception -based model that considers image degradation as perceived change in structural information, while also incorporating important perceptual ...

  6. Medoid - Wikipedia

    en.wikipedia.org/wiki/Medoid

    Euclidean distance is a standard distance metric used to measure the dissimilarity between two points in a multi-dimensional space. In the context of text data, documents are often represented as high-dimensional vectors, such as TF vectors, and the Euclidean distance can be used to measure the dissimilarity between them.

  7. Ridge detection - Wikipedia

    en.wikipedia.org/wiki/Ridge_detection

    In image processing, ridge detection is the attempt, via software, to locate ridges in an image, defined as curves whose points are local maxima of the function, akin to geographical ridges. For a function of N variables, its ridges are a set of curves whose points are local maxima in N − 1 dimensions.

  8. 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 ...

  9. Depth of field - Wikipedia

    en.wikipedia.org/wiki/Depth_of_field

    Therefore, the blue channel will have a greater depth of field than the other colours. The image processing identifies blurred regions in the red and green channels and in these regions copies the sharper edge data from the blue channel. The result is an image that combines the best features from the different f-numbers. [26]