Regular Section
Learning Deep Dictionary for Hyperspectral Image Denoising
2015 Volume E98.D Issue 7 Pages 1401-1404
Details
2015 Volume E98.D Issue 7 Pages 1401-1404
Using traditional single-layer dictionary learning methods, it is difficult to reveal the complex structures hidden in the hyperspectral images. Motivated by deep learning technique, a deep dictionary learning approach is proposed for hyperspectral image denoising, which consists of hierarchical dictionary learning, feature denoising and fine-tuning. Hierarchical dictionary learning is helpful for uncovering the hidden factors in the spectral dimension, and fine-tuning is beneficial for preserving the spectral structure. Experiments demonstrate the effectiveness of the proposed approach.
