Optimization Methods for Convolutional Sparse Coding

Understand

Sparse and convolutional constraints form a natural prior for many optimization problems that arise from physical processes.

• Detecting motifs in speech and musical passages, super-resolving images, compressing videos, and reconstructing harmonic motions can all leverage redundancies introduced by convolution.
• Solving problems involving sparse and convolutional constraints remains a difficult computational problem, however.
• In this paper we present an overview of convolutional sparse coding in a consistent framework.