Matches in DBpedia 2016-04 for { ?s ?p "The lifting scheme is a technique for both designing wavelets and performing the discrete wavelet transform.Actually it is worthwhile to merge these steps and design the wavelet filters while performing the wavelet transform.This is then called the second generation wavelet transform.The technique was introduced by Wim Sweldens.Factorizes orthogonal and biorthogonal wavelet transforms into elementary spatial operators called lifting. It has two main applications. The first one is an acceleration of the fast wavelet transform algorithm. The filter bank convolution and subsampling operations are factorized into elementary filterings on even and odd samples, which reduces the number of operations by nearly 2. Border treatments are also simplified. This is also called a paraunitary filter bank implementation. The second application is the design of wavelets adapted to multidimensional bounded domains and surfaces, which is not possible with a Fourier transform approach. The discrete wavelet transform applies several filters separately to the same signal.In contrast to that, for the lifting scheme the signal is divided like a zipper.Then a series of convolution-accumulate operations across the divided signals is applied."@en }
Showing triples 1 to 2 of
2
with 100 triples per page.
- Lifting_scheme abstract "The lifting scheme is a technique for both designing wavelets and performing the discrete wavelet transform.Actually it is worthwhile to merge these steps and design the wavelet filters while performing the wavelet transform.This is then called the second generation wavelet transform.The technique was introduced by Wim Sweldens.Factorizes orthogonal and biorthogonal wavelet transforms into elementary spatial operators called lifting. It has two main applications. The first one is an acceleration of the fast wavelet transform algorithm. The filter bank convolution and subsampling operations are factorized into elementary filterings on even and odd samples, which reduces the number of operations by nearly 2. Border treatments are also simplified. This is also called a paraunitary filter bank implementation. The second application is the design of wavelets adapted to multidimensional bounded domains and surfaces, which is not possible with a Fourier transform approach. The discrete wavelet transform applies several filters separately to the same signal.In contrast to that, for the lifting scheme the signal is divided like a zipper.Then a series of convolution-accumulate operations across the divided signals is applied.".
- Q3238415 abstract "The lifting scheme is a technique for both designing wavelets and performing the discrete wavelet transform.Actually it is worthwhile to merge these steps and design the wavelet filters while performing the wavelet transform.This is then called the second generation wavelet transform.The technique was introduced by Wim Sweldens.Factorizes orthogonal and biorthogonal wavelet transforms into elementary spatial operators called lifting. It has two main applications. The first one is an acceleration of the fast wavelet transform algorithm. The filter bank convolution and subsampling operations are factorized into elementary filterings on even and odd samples, which reduces the number of operations by nearly 2. Border treatments are also simplified. This is also called a paraunitary filter bank implementation. The second application is the design of wavelets adapted to multidimensional bounded domains and surfaces, which is not possible with a Fourier transform approach. The discrete wavelet transform applies several filters separately to the same signal.In contrast to that, for the lifting scheme the signal is divided like a zipper.Then a series of convolution-accumulate operations across the divided signals is applied.".