We show that these adaptive schemes yield lower entropies than schemes with fixed update filters, a property that is highly relevant in the context of ...
The basic idea is to choose the update filters according to some decision criterion which depends on the local characteristics of the input signal. We show that ...
Dec 5, 2024 · The basic idea is to choose the update filters according to some decision criterion which depends on the local characteristics of the input ...
The current paper discusses the effects of quantization in such an adaptive wavelet decomposition. We provide conditions for recovering the original decisions ...
Classical linear wavelet representations of images have the drawback that they are not optimally suited to represent edge information. To overcome this problem, ...
We introduce an autoencoder wavelet transform network that is trained using gradient descent. We show that the model is capable of learning structured wavelet ...
Gradient-driven update lifting for adaptive wavelets. 1 Oct 2005 | Signal ... Seismic denoising using adaptive wiener filter in redundant-lifting wavelet domain.
Oct 22, 2024 · This paper treats a class of adaptive update lifting schemes which do not require bookkeeping for perfect reconstruction.
The lifting scheme provides a new, spatial intuition into the wavelet transform that simplifies the introduction of adaptivity and nonlinearities, ...
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In this paper we present a new image interpolation algorithm based on the adaptive update lifting scheme. This scheme allows us to build adaptive wavelets ...