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  2. 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 ...

  3. Digital image correlation and tracking - Wikipedia

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

    DVC can be performed using volumetric image datasets. These images can be obtained using confocal microscopy, X-ray computed tomography, Magnetic Resonance Imaging or other techniques. Similar to the other DIC techniques, the images must exhibit a distinct, high-contrast 3D "speckle pattern" to ensure accurate displacement measurement. [10]

  4. Template matching - Wikipedia

    en.wikipedia.org/wiki/Template_matching

    For example, if an algorithm is looking for a face, its template eigenspaces may consist of images (i.e., templates) of faces in different positions to the camera, in different lighting conditions, or with different expressions (i.e., poses). It is also possible for a matching image to be obscured or occluded by an object.

  5. 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 ...

  6. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    A similarity measure can take many different forms depending on the type of data being clustered and the specific problem being solved. One of the most commonly used similarity measures is the Euclidean distance, which is used in many clustering techniques including K-means clustering and Hierarchical clustering. The Euclidean distance is a ...

  7. SimRank - Wikipedia

    en.wikipedia.org/wiki/SimRank

    SimRank is a general similarity measure, based on a simple and intuitive graph-theoretic model.SimRank is applicable in any domain with object-to-object relationships, that measures similarity of the structural context in which objects occur, based on their relationships with other objects.

  8. Content-based image retrieval - Wikipedia

    en.wikipedia.org/wiki/Content-based_image_retrieval

    The most common method for comparing two images in content-based image retrieval (typically an example image and an image from the database) is using an image distance 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 ...

  9. Semantic similarity - Wikipedia

    en.wikipedia.org/wiki/Semantic_similarity

    Similarity learning can often outperform predefined similarity measures. Broadly speaking, these approaches build a statistical model of documents, and use it to estimate similarity. LSA (latent semantic analysis): [44] [45] (+) vector-based, adds vectors to measure multi-word terms; (−) non-incremental vocabulary, long pre-processing times

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