Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Improvement of conventional deinterlacing methods with extrema detection and interpolation

International audienceThis article presents a new algorithm for spatial deinterlacing that could easily be integrated in a more complete deinterlacing system, typically a spatio-temporal motion adaptive one. The spatial interpolation part often fails to reconstruct close to horizontal lines with a proper continuity, leading to highly visible artifacts. Our system preserves the structure continuity taking into account that the mis-interpolated points usually correspond to local value extrema. The processing is based on chained lists and connected graph construction. The new interpolation method is restricted to such structures, for the rest of the image, a proper traditional directional spatial interpolation gives satisfactory results already. Although the number of pixels affected by the extrema interpolation is relatively small, the overall image quality is subjectively well improved. Moreover, our solution allows to gain back one of the major advantages of motion compensation methods, without having to afford their complexity cost