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Found 6 papers, 1 papers with code
The Parallel Algorithm for the 2-D Discrete Wavelet Transform
Until now, the transform on general-purpose processors (CPUs) was mostly computed using a separable lifting scheme.
Accelerating Discrete Wavelet Transforms on GPUs
The two-dimensional discrete wavelet transform has a huge number of applications in image-processing techniques.
Compression Artifacts Removal Using Convolutional Neural Networks
This paper shows that it is possible to train large and deep convolutional neural networks (CNN) for JPEG compression artifacts reduction, and that such networks can provide significantly better reconstruction quality compared to previously used smaller networks as well as to any other state-of-the-art methods.
Parallel Wavelet Schemes for Images
In this paper, we introduce several new schemes for calculation of discrete wavelet transforms of images.
CNN for License Plate Motion Deblurring
In this work we explore the previously proposed approach of direct blind deconvolution and denoising with convolutional neural networks in a situation where the blur kernels are partially constrained.
