6533b85efe1ef96bd12c05b9
RESEARCH PRODUCT
Non-consistent cell-average multiresolution operators with application to image processing
Francesc AràndigaDionisio F. Yáñezsubject
Polynomial regressionDecimationTheoretical computer scienceApplied MathematicsInpaintingImage processing010103 numerical & computational mathematics01 natural sciences010101 applied mathematicsComputational MathematicsOperator (computer programming)Consistency (statistics)0101 mathematicsRepresentation (mathematics)AlgorithmMathematicsImage compressiondescription
In recent years different techniques to process signal and image have been designed and developed. In particular, multiresolution representations of data have been studied and used successfully for several applications such as compression, denoising or inpainting. A general framework about multiresolution representation has been presented by Harten (1996) 20. Harten's schemes are based on two operators: decimation, D , and prediction, P , that satisfy the consistency property D P = I , where I is the identity operator. Recently, some new classes of multiresolution operators have been designed using learning statistical tools and weighted local polynomial regression methods obtaining filters that do not satisfy this condition. We show some proposals to solve the consistency problem and analyze its properties. Moreover, some numerical experiments comparing our methods with the classical methods are presented.
year | journal | country | edition | language |
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2016-01-01 | Applied Mathematics and Computation |