@InProceedings{SautterRosa:2017:ImGrPa,
author = "Sautter, Rubens Andreas and Rosa, Reinaldo Roberto",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)}",
title = "Improvement to Gradient Pattern Analysis and applications",
booktitle = "Anais...",
year = "2017",
organization = "Workshop dos Cursos de Computa{\c{c}}{\~a}o Aplicada do INPE,
17. (WORCAP)",
keywords = "Sistemas Din{\^a}micos, Morfologia de gal{\'a}xias, GPU.",
abstract = "The description of complex patterns, especially spatial patterns,
is a challenge. Some features, such as classification features(in
static cases) and regime (in dynamical systems), are difficult to
detect. In this work we present the Gradient Pattern Analysis
(GPA), an operator that describes spatially extended system by
means of vectorial alignment and vectorial symmetry. This operator
showed interesting results dynamical systems [1] and astronomical
problems[2, 3]. We briefly review this operator and propose some
improvements, with respect to the measured feature and the
computation cost. To improve the feature extraction, we introduce
an operator which analyses the second order gradient moment. To
reduce the computation time, a version of this code is presented
using OpenCL. In this work we also briefly showcase two
applications to this operator: Coupled Map Lattices (CML) and
galaxy morphological classification. As result we observed better
results with the improved operator and a lower computational cost
in the parallel version.",
conference-location = "S{\~a}o Jos{\'e} dos Campos, SP",
conference-year = "20-22 nov. 2017",
language = "en",
targetfile = "Sautter_improvement.pdf",
urlaccessdate = "15 jun. 2024"
}