Topic
Harmonic wavelet transform
About: Harmonic wavelet transform is a research topic. Over the lifetime, 9602 publications have been published within this topic receiving 247336 citations.
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SIDI1
TL;DR: A simulation study is presented to demonstrate the ability of the wavelet transform based on Paul wavelet algorithm to provide, with a good accuracy, a phase distribution from a single image without unwrapping step.
99 citations
TL;DR: The experimental results demonstrate that the ripplet transform can provide efficient representation of edges in images and holds great potential for image processing such as image restoration, image denoising and image compression.
99 citations
TL;DR: A new locally adaptive wavelet transform, called easy path wavelettransform (EPWT), that works along pathways through the array of function values and exploits the local correlations of the data in a simple appropriate manner is introduced.
Abstract: We introduce a new locally adaptive wavelet transform, called easy path wavelet transform (EPWT), that works along pathways through the array of function values and exploits the local correlations of the data in a simple appropriate manner. The usual discrete orthogonal and biorthogonal wavelet transform can be formulated in this approach. The EPWT can be incorporated into a multiresolution analysis structure and generates data dependent scaling spaces and wavelet spaces. Numerical results show the enormous efficiency of the EPWT for representation of two-dimensional data.
99 citations
Patent•
25 Nov 2003
TL;DR: In this paper, a method for acquiring two or more two-dimensional Fourier transforms from different perspectives of a three-dimensional object region was described, which can then be constructed using tomographic methods, permitting the application of image analysis algorithms analogous to those used for 2D images.
Abstract: A method is described for acquiring two or more two-dimensional Fourier transforms from different perspectives of a three-dimensional object region (9). A three-dimensional Fourier transform can then be constructed using tomographic methods, permitting the application of image analysis algorithms (52) analogous to those used for two-dimensional images.
99 citations
TL;DR: A critical wavelet coefficient quantification is defined, i.e., the coarsest quantification that allows perfect reconstruction for the Haar transform and for arbitrarily smooth wavelet transforms derived from it, allowing implementation of multiresolution subband compression schemes.
Abstract: Signal compression can be obtained by wavelet transformation of integer input data followed by quantification and coding. As the quantification is usually lossy, the whole compression/decompression scheme is lossy too. We define a critical wavelet coefficient quantification, i.e., the coarsest quantification that allows perfect reconstruction. This is demonstrated for the Haar transform and for arbitrarily smooth wavelet transforms derived from it. The new integer wavelet transform allows implementation of multiresolution subband compression schemes, in which the decompressed data are gradually refined, retaining the option of perfect reconstruction.
98 citations