Abstract
A quantitative measure of diversity D(A, B) between two images, A and B, is desirable for a good number of practical applications, as for instance:
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For assessing the effectiveness of image restoration methods. Restored images B are matched with the unimpaired image A, and low values of D(A, B) characterize the better methods.
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For comparing the results of two image partitions obtained by means of two segmentation methods. One of these partitions can be the ground-truth segmentation, if known.
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For comparing the results of two edge detectors yielding two different edge images. If the edge detection is performed upon a noisy image, in many cases the edges extracted from the noiseless image represent a good ground-truth edge image, which can be used as a template for assessing the performance of the edge detector. The immediate edge detector outputs are grey-scale images; thus, thresholding and cleaning operations, which would be necessary for obtaining binary edge maps, need not to be involved in the matching process.
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For measuring the amount of deformation of an image with respect to a reference one. Impairments can be originated by fluctuating performances of the imaging device, while geometrical deformations can be caused by changes of the viewing position.
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For assessing the performance of lossy image coding methods, by comparing the original with the decoded image.
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© 1995 Springer-Verlag Berlin Heidelberg
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Zamperoni, P., Starovoitov, V. (1995). How dissimilar are two grey-scale images?. In: Sagerer, G., Posch, S., Kummert, F. (eds) Mustererkennung 1995. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79980-8_53
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DOI: https://doi.org/10.1007/978-3-642-79980-8_53
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