Publicado 12 números por año
ISSN Imprimir: 0040-2508
ISSN En Línea: 1943-6009
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NEURAL NETWORK BASED DETECTION OF HETEROGENEITIES IN NOISY IMAGES
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SINOPSIS
Many methods of image processing include a stage of detecting heterogeneities (edges, small sizes objects, textures). It is often difficult to reach efficient detection due to noise presence in analyzed images when conventional detectors fail. Neural networks are tools that allow to partly improve detectability of heterogeneities due to joint use (aggregation) of elementary detectors. Performance can be improved due to proper selection of elementary detectors as well as pre-processing (pre-filtering) or post-processing (aggregation of detection results). In this paper, we consider some of aforementioned aspects and give examples of neural network learning and application to different test and real life images.
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