Gradient extraction operators for discrete interval-valued data

Digital images are generally created as discrete measurements of light, as performed by dedicated sensors. Consequently, each pixel contains a discrete approximation of the light inciding in a sensor element. The nature of this measurement implies certain uncertainty due to discretization matters. In this work we propose to model such uncertainty using intervals, further leading to the generation of so-called interval-valued images. Then, we study the partial differentiation of such images, putting a spotlight on antisymmetric convolution operators for such task. Finally, we illustrate the utility of the interval-valued images by studying the behaviour of an extended version of the well-known Canny edges detection method

Gradient extraction operators for discrete interval-valued data

Digital images are generally created as discrete measurements of light, as performed by dedicated sensors. Consequently, each pixel contains a discrete approximation of the light inciding in a sensor element. The nature of this measurement implies certain uncertainty due to discretization matters. In this work we propose to model such uncertainty using intervals, further leading to the generation of so-called interval-valued images. Then, we study the partial differentiation of such images, putting a spotlight on antisymmetric convolution operators for such task. Finally, we illustrate the utility of the interval-valued images by studying the behaviour of an extended version of the well-known Canny edges detection method

A bilateral schema for interval-valued image differentiation

Differentiation of interval-valued functions is an intricate problem, since it cannot be defined as a direct generalization of differentiation of scalar ones. Literature on interval arithmetic contains proposals and definitions for differentiation, but their semantic is unclear for the cases in which intervals represent the ambiguity due to hesitancy or lack of knowledge. In this work we analyze the needs, tools and goals for interval-valued differentiation, focusing on the case of interval-valued images. This leads to the formulation of a differentiation schema inspired by bilateral filters, which allows for the accommodation of most of the methods for scalar image differentiation, but also takes support from interval-valued arithmetic. This schema can produce area-, segment-and vector-valued gradients, according to the needs of the image processing task it is applied to. Our developments are put to the test in the context of edge detection

Detecao de Bordas baseada em Morfologia Matemática Fuzzy Intervalar e as Funcoes de Agregacao K

Edge detection is a digital image processing tool. It determines points in a digital image where light intensity suddenly changes. This process applies to a digital image which assumes some degree of uncertainty in the location and intensity of the pixel in the real image. In this work, we propose an edge detection model which consists in capturing this uncertainty in terms of interval images. Then we apply interval-valued fuzzy morphology to calculate the interval-valued erosion and dilation. Finally, we compute the convex combinations of the upper and lower bounds of the interval-valued erosion and dilation image, to obtain a morphological erosion and dilation respectively, and thus an edge image.A deteccao de bordas é uma ferramenta de processamento digital de imagenes. Ela determina pontos de uma imagem digital onde a intensidade da luz muda repentinamente. Esse processo aplica-se a uma imagem digital a qual supoe algum grau de incerteza na localizacao e na intensidade do pixel da imagem real. Neste trabalho, é proposto um modelo de detecao de bordas que consiste na captura dessa incerteza em termos de imagens intervalares, para depois aplicar a erosao e dilatacao intervalar fuzzy. Finalmente, por meio de uma combinacao convexa sobre os limites superiores e inferiores da erosao e a dilatacao intervalar, sao obtidas a erosao e a dilatacao morfológica respectivamente, com as quais se faz possível produzir uma imagem borda