Convolutional sparse coding explicitly models local interactions through the convolution operator, however the resulting optimization problem is considerably more complex than traditional sparse coding. In this paper, we draw upon ideas from signal processing and Augmented Lagrange Methods (ALMs) to produce...
Fast Convolutional Sparse Coding in the Dual Domain Convolutional sparse coding (CSC) is an important building block of many computer vision applications ranging from image and video compression to deep learning. We present two contributions to the state of the art in CSC. First, we significantly ...
Sˇ roubek, "Fast convolutional sparse coding using matrix inversion lemma," Dig- ital Signal Processing, vol. 55, pp. 44-51, 2016. doi:10.1016/j.dsp.2016.04.012M. Sorel and F. Sroubek, "Fast convolutional sparse coding using matrix inversion lemma," Digital Signal Processing, vol. 55...
convolutional sparse coding (CSC)deep learningseismic inversionsparse reflectivityIn sparse coding, we attempt to extract features of input vectors, assuming that the data is inherently structured as a sparse superposition of basic building blocks. Similarly, neural networks perform a given task by ...
By contrast, the Convolutional Sparse Coding (CSC) model treats the signals globally and, therefore, has shown superior performance over patch-based methods in several image processing applications. Here, we propose the use of CSC model for seismic data denoising. In particular, we use the Local...
Image super-resolution with fast approximate convolutional sparse coding. In International Conference on Neural Information Processing, pages 250-257. Springer, 2014.C. Osendorfer, H. Soyer, and P. Van Der Smagt, "Image super-resolution with fast approximate convolutional sparse coding," in ...
By contrast, the Convolutional Sparse Coding (CSC) model treats the signals globally and, therefore, has shown superior performance over patch-based methods in several image processing applications. Here, we propose the use of CSC model for seismic data denoising. In particular, we use the Local...
Brendt Wohlberg会议论文Erik Skau and Brendt Wohlberg. A Fast Parallel Algorithm for Convolutional Sparse Coding. In IEEE Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), 2018. ISBN 9781538609514. doi: 10.1109/IVMSPW.2018.8448536....
further refined the model, introducing a Fast and Flexible Denoising Convolutional Neural Network (FFDNet) [15]. This innovation, building upon the foundation of the DnCNN model, incorporates a noise level map as an additional input, thereby augmenting the model’s adaptability to diverse noise ...
further refined the model, introducing a Fast and Flexible Denoising Convolutional Neural Network (FFDNet) [15]. This innovation, building upon the foundation of the DnCNN model, incorporates a noise level map as an additional input, thereby augmenting the model’s adaptability to diverse noise ...