INVESTIGADORES
CAIAFA Cesar Federico
capítulos de libros
Título:
Tensor methods for low-level vision
Autor/es:
TATSUYA YOKOTA; CESAR F. CAIAFA; QIBIN ZHAO
Libro:
Tensors for Data Processing
Editorial:
Elsevier
Referencias:
Lugar: London; Año: 2021; p. 371 - 425
Resumen:
Low-level vision is a processing system that plays an important role in human as well as in machine visual pattern recognition. It is often used to refer to information processing based on local visual features such as edges, corners, colors, and self-similarity. Typical examples in the research fields of computer vision and image/ signal processing are compression, noise removal, deblurring, superresolution, image inpainting, computed tomography, and compressed sensing. In this chapter, we introduce the tensor representations, mathematical models, and optimization algorithms and illustrate their application to selected low-level vision tasks.
