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oai:docta.ucm.es:20.500.14352/194732024-11-26T17:05:32Zcom_20.500.14352_14col_20.500.14352_21

Gradient Fusion Operators for Vector-Valued Image Processing López Molina, Carlos Montero De Juan, Francisco Javier Bustince, Humberto De Baets, Bernard Olaso, Pablo Rojas Patuelli, Karina Gómez González, Daniel Montero De Juan, Francisco Javier 510.6 Vector-valued images Differentiation Jacobian matrix Information fusion Lógica simbólica y matemática (Matemáticas) 1102.14 Lógica Simbólica International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets Proceedings of the Conference of the European Society for Fuzzy Logic and Technology While classical image processing algorithms were designed for scalar-valued (binary or grayscale) images, new technologies have made it commonplace to work with vector-valued ones. These technologies can involve new types of sensors, as in remote sensing, but also mathematical models leading to an increased cardinality at each pixel. This work analyzes the role of first-order differentiation in vector-valued images; specifically, we explore a novel operator to produce a 2D vector from a Jacobian matrix, in order to represent the variation in a vector-valued image as a planar feature. Depto. de Estadística e Investigación Operativa Fac. de Ciencias Matemáticas TRUE pub 2023-06-18T00:22:29Z 2023-06-18T00:22:29Z 2017 book part https://hdl.handle.net/20.500.14352/19473 XXXX-XXXX 10.1007/978-3-319-66824-6 38 eng Advances in Intelligent Systems and Computing Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K.T., Krawczak, M. eds: Advances in Fuzzy Logic and Technology 2017. Springer International Publishing, Cham (2018) restricted access application/pdf Springer