An adaptive perception-based image preprocessing method

The aim of this paper is to introduce an adaptive preprocessing procedure based on human perception in order to increase the performance of some standard image processing techniques. Specifically, image frequency content has been weighted by the corresponding value of the contrast sensitivity function, in agreement with the sensitiveness of human eye to the different image frequencies and contrasts. The 2D Rational dilation wavelet transform has been employed for representing image frequencies. In fact, it provides an adaptive and flexible multiresolution framework, enabling an easy and straightforward adaptation to the image frequency content. Preliminary experimental results show that the proposed preprocessing allows us to increase the performance of some standard image enhancement algorithms in terms of visual quality and often also in terms of PSNR

A Panorama on Multiscale Geometric Representations, Intertwining Spatial, Directional and Frequency Selectivity

The richness of natural images makes the quest for optimal representations in image processing and computer vision challenging. The latter observation has not prevented the design of image representations, which trade off between efficiency and complexity, while achieving accurate rendering of smooth regions as well as reproducing faithful contours and textures. The most recent ones, proposed in the past decade, share an hybrid heritage highlighting the multiscale and oriented nature of edges and patterns in images. This paper presents a panorama of the aforementioned literature on decompositions in multiscale, multi-orientation bases or dictionaries. They typically exhibit redundancy to improve sparsity in the transformed domain and sometimes its invariance with respect to simple geometric deformations (translation, rotation). Oriented multiscale dictionaries extend traditional wavelet processing and may offer rotation invariance. Highly redundant dictionaries require specific algorithms to simplify the search for an efficient (sparse) representation. We also discuss the extension of multiscale geometric decompositions to non-Euclidean domains such as the sphere or arbitrary meshed surfaces. The etymology of panorama suggests an overview, based on a choice of partially overlapping "pictures". We hope that this paper will contribute to the appreciation and apprehension of a stream of current research directions in image understanding.Comment: 65 pages, 33 figures, 303 reference

Gröbner bases and wavelet design

AbstractIn this paper, we detail the use of symbolic methods in order to solve some advanced design problems arising in signal processing. Our interest lies especially in the construction of wavelet filters for which the usual spectral factorization approach (used for example to construct the well-known Daubechies filters) is not applicable. In these problems, we show how the design equations can be written as multivariate polynomial systems of equations and accordingly how Gröbner algorithms offer an effective way to obtain solutions in some of these cases

Constant-Q Transform Toolbox for Music Processing

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Wavelets and Subband Coding

First published in 1995, Wavelets and Subband Coding offered a unified view of the exciting field of wavelets and their discrete-time cousins, filter banks, or subband coding. The book developed the theory in both continuous and discrete time, and presented important applications. During the past decade, it filled a useful need in explaining a new view of signal processing based on flexible time-frequency analysis and its applications. Since 2007, the authors now retain the copyright and allow open access to the book

VIBRATION FEATURE EXTRACTION METHODS FOR GEAR FAULTS DIAGNOSIS -A REVIEW

The key point of condition monitoring and fault diagnosis of gearboxes is a fault feature extraction. The study of fault feature detection in rotating machinery from vibration analysis and diagnosis has attracted sustained attention during past decades. In most cases determination of the condition of a gearbox requires study of more than one feature or a combination of several techniques. This paper attempts to survey and summarize the recent research and development of feature extraction methods for gear fault diagnosis, providing references for researchers concerning with this topic and helping them identify further research topics. First, the feature extraction methods for gear faults diagnosis are briefly introduced, the usefulness of the method is illustrated and the problems and the corresponding solutions are listed. Then, recent applications of feature extraction methods for gear faults diagnosis are summarized, in terms of industrial gearboxes. Finally, the open problems of feature extraction methods for gear fault diagnosis are discussed and potential future research directions are identified. It is expected that this review will serve as an introduction summary of vibration feature extraction methods for gear faults diagnosis for those new to the concepts of its applications to gear fault diagnosis based on vibratio