6533b85efe1ef96bd12c05b9

RESEARCH PRODUCT

Non-consistent cell-average multiresolution operators with application to image processing

Francesc AràndigaDionisio F. Yáñez

subject

Polynomial regressionDecimationTheoretical computer scienceApplied MathematicsInpaintingImage processing010103 numerical & computational mathematics01 natural sciences010101 applied mathematicsComputational MathematicsOperator (computer programming)Consistency (statistics)0101 mathematicsRepresentation (mathematics)AlgorithmMathematicsImage compression

description

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.

https://doi.org/10.1016/j.amc.2015.08.074