International Journal of Wavelets, Multiresolution and Information Processing 

About: International Journal of Wavelets, Multiresolution and Information Processing is an academic journal published by World Scientific. The journal publishes majorly in the area(s): Wavelet & Wavelet transform. It has an ISSN identifier of 0219-6913. Over the lifetime, 1177 publications have been published receiving 10339 citations. The journal is also known as: IJWMIP & Wavelets, multiresolution and information processing..

Demodulation by complex-valued wavelets for stochastic pattern recognition

Abstract: Samples from stochastic signals having sufficient complexity need reveal only a little unexpected shared structure, in order to reject the hypothesis that they are independent. The mere failure of a test of statistical independence can thereby serve as a basis for recognizing stochastic patterns, provided they possess enough degrees-of-freedom, because all unrelated ones would pass such a test. This paper discusses exploitation of this statistical principle, combined with wavelet image coding methods to extract phase descriptions of incoherent patterns. Demodulation and coarse quantization of the phase information creates decision environments characterized by well-separated clusters, and this lends itself to rapid and reliable pattern recognition.

The timing of facial motion in posed and spontaneous smiles

Abstract: Almost all work in automatic facial expression analysis has focused on recognition of prototypic expressions rather than dynamic changes in appearance over time. To investigate the relative contribution of dynamic features to expression recognition, we used automatic feature tracking to measure the relation between amplitude and duration of smile onsets in spontaneous and deliberate smiles of 81 young adults of Euro- and African-American background. Spontaneous smiles were of smaller amplitude and had a larger and more consistent relation between amplitude and duration than deliberate smiles. A linear discriminant classifier using timing and amplitude measures of smile onsets achieved a 93% recognition rate. Using timing measures alone, recognition rate declined only marginally to 89%. These findings suggest that by extracting and representing dynamic as well as morphological features, automatic facial expression analysis can begin to discriminate among the message values of morphologically similar expressions.

Empirical mode decompositions as data-driven wavelet-like expansions

Abstract: Huang's data-driven technique of Empirical Mode Decomposition (EMD) is applied to the versatile, broadband, model of fractional Gaussian noise (fGn). The experimental spectral analysis and statistical characterization of the obtained modes reveal an equivalent filter bank structure which shares most properties of a wavelet decomposition in the same context, in terms of self-similarity, quasi-decorrelation and variance progression. Furthermore, the spontaneous adaptation of EMD to "natural" dyadic scales is shown, rationalizing the method as an alternative way for estimating the fGn Hurst exponent.

Infrared and visible image fusion with convolutional neural networks

Abstract: The fusion of infrared and visible images of the same scene aims to generate a composite image which can provide a more comprehensive description of the scene. In this paper, we propose an infrared...

The uncertainty principle associated with the continuous shearlet transform

Abstract: Finding optimal representations of signals in higher dimensions, in particular directional representations, is currently the subject of intensive research. Since the classical wavelet transform does not provide precise directional information in the sense of resolving the wavefront set, several new representation systems were proposed in the past, including ridgelets, curvelets and, more recently, Shearlets. In this paper we study and visualize the continuous Shearlet transform. Moreover, we aim at deriving mother Shearlet functions which ensure optimal accuracy of the parameters of the associated transform. For this, we first show that this transform is associated with a unitary group representation coming from the so-called Shearlet group and compute the associated admissibility condition. This enables us to employ the general uncertainty principle in order to derive mother Shearlet functions that minimize the uncertainty relations derived for the infinitesimal generators of the Shearlet group: scaling, shear and translations. We further discuss methods to ensure square-integrability of the derived minimizers by considering weighted L2-spaces. Moreover, we study whether the minimizers satisfy the admissibility condition, thereby proposing a method to balance between the minimizing and the admissibility property.