Anzeige
Erschienen in:
2011 | OriginalPaper | Buchkapitel
Regularization with Adaptive Neighborhood Condition for Image Denoising
verfasst von : Felix Calderon, Carlos A. Júnez–Ferreira
Erschienen in: Advances in Soft Computing
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Image denoising by minimizing a similarity of neighborhood-based cost function is presented. This cost function consists of two parts, one related to data fidelity and the other is a structure preserving smoothing term. The latter is controlled by a weight coefficient that measures the neighborhood similarity between two pixels and attaching an additional term penalizes it. Unlike most work in noise removal area, the weight of each pixel within the neighborhood is not defined by a Gaussian function. The obtained results show a good performance of our proposal, compared with some state-of-the-art algorithms.