Regularization Parameter-Free Convolutional Sparse Coding via Projections Onto The ℓ1-Ball and The Discrepancy Principle

Given a set of dictionary filters, the most widely used formulation of the convolutional sparse coding (CSC) problem is convolutional basis pursuit denoising (CBPDN), in which an image is represented as a sum over a set of convolutions of coefficient maps. When the input image is noisy, CBPDN's...

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Bibliographic Details

Published in:	2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP) pp. 1 - 6
Main Author:	Rodriguez, Paul
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.09.2018
Subjects:	Convolution Convolutional codes Convolutional sparse coding Encoding Estimation Image coding Image reconstruction Lasso Morozov's discrepancy principle Signal to noise ratio
Online Access:	Get full text
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