Adaptive morphological filters based on a multiple orientation vector field dependent on image local features.

Abstract : This paper addresses the formulation of adaptive morphological filters based on spatially-variant structuring elements. The adaptivity of these filters is achieved by modifying the shape and orientation of the structuring elements according to a multiple orientation vector field. This vector field is provided by means of a bank of directional openings which can take into account the possible multiple orientations of the contours in the image. After reviewing and formalizing the definition of the spatially-variant dilation, erosion, opening and closing, the proposed structuring elements are described. These spatially-variant structuring elements are based on ellipses which vary over the image domain adapting locally their orientation according to the multiple orientation vector field and their shape (the eccentricity of the ellipses) according to the distance to relevant contours of the objects. The proposed adaptive morphological filters are used on gray-level images and are compared with spatially-invariant filters, with spatially-variant filters based on a single orientation vector field, and with adaptive morphological bilateral filters. Results show that the morphological filters based on a multiple orientation vector field are more adept at enhancing and preserving structures which contains more than one orientation.
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Journal of Computational and Applied Mathematics, Elsevier, 2018, 330, pp.965 - 981. 〈10.1016/j.cam.2017.05.001〉
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Álvar-Ginés Legaz-Aparicio, Rafael Verdu-Monedero, Jesus Angulo. Adaptive morphological filters based on a multiple orientation vector field dependent on image local features.. Journal of Computational and Applied Mathematics, Elsevier, 2018, 330, pp.965 - 981. 〈10.1016/j.cam.2017.05.001〉. 〈hal-01688889〉

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