We present wavelet warping — a new class of forward 3D warping algorithms for image-based rendering. In wavelet warping most of the warping operation is performed in the wavelet domain, by operating on the coefficients of the wavelet transforms of the images and other matrices defined by the mapping. Operating in this fashion is often more efficient than performing the 3D warp in the standard m...

This paper presents a novel and computationally efficient approach to an adaptive mammographic image feature enhancement using wavelet-based multiresolution analysis. Upon wavelet decomposition applied to a given mammographic image, we integrate the information of the tree-structured zerocrossings of wavelet coefficients and the information of the low-pass filtered subimage to enhance the desir...

A novel and computationally efficient approach to an adaptive mammographic image feature enhancement using wavelet-based multiresolution analysis is presented. On wavelet decomposition applied to a given mammographic image, we integrate the information of the tree-structured zero crossings of wavelet coefficients and the information of the low-pass-filtered subimage to enhance the desired image...

Abstract This research sheds light on the causal link between commodity price indexes, i.e., Agricultural Raw Materials Price Index, Industry Input Metal and Energy in global market, using wavelet coherence, Toda–Yamamoto causality, gradual shift causality tests over period 1992M1 to 2019M12. Findings from power spectrum partial coherence reveal that: (1) there was significant volatility Index ...

Introduction: Multidimensional magnetic resonance spectroscopy (MRS) can provide additional information at the expense of longer acquisition time than 1D MRS. Assuming 2D MRS is sparse in wavelet domain, Iddo[1] first introduced compressed sensing (CS) [2,3] to reconstruct multidimensional MRS from partial and random free induction decay (FID) data. However, the darkness in 1D MRS derives from ...

Light field techniques allow the rendering of objects in time complexity unrelated to their geometric complexity. The technique discretely samples the space of light rays exiting the boundary around an object and then reconstructs a requested view from these data. In order to generate high quality images a dense sampling of the space is required which leads to large data sets. These data sets e...

Abstract Time–frequency localization of model-data discrepancies may provide useful information for climate models inter-comparison, and especially the goals model refinement improvement. CMIP5 long-term historical (1850–2005) run experiment are compared using wavelet-based multiscale descriptive diagnostic techniques with interesting results. Wavelet coherence maps can visualize ability altern...

A network of spinal neurons known as central pattern generator (CPG) produces the rhythmic motor patterns required for coordinated swimming, walking, and running in mammals. Because the output of this network varies with time, its analysis cannot be performed by statistical methods that assume data stationarity. The present work uses short-time Fourier (STFT) and wavelet-transform (WT) algorith...

In previous work it was established that asymptotic incoherence can be used to facilitate subsampling in a variety of continuous compressed sensing problems and the coherence structure of certain onedimensional Fourier sampling problems was determined. This paper extends the analysis of asymptotic incoherence to cover multidimensional reconstruction problems. It is shown that Fourier sampling a...