Jul 17, 2019 · Multispectral image encoding/decoding methods using spectral dictionary learning and sparse representation to fully exploit spectral features are proposed.
We propose that both colorimetric and spectral distortion in compressed multispectral images can be reduced by a composite model, named OLCP(W)-X ...
This paper proposes a multi-aperture multispectral imaging system based on notch filters that overcomes this limitation by allowing light from most of the ...
We propose a novel generative adversarial network (GAN) based prediction method called MultiTempGAN for compression of multitemporal MS images.
Hyperspectral imaging is beneficial in a diverse range of applications from diagnostic medicine, to agriculture, to surveillance to name a few.
This study proposes a novel approach to dictionary learning based on nonlinear unmixing for dense mixtures and linear unmixing for sparse mixtures. Additionally ...
May 10, 2017 · This paper proposes a novel method of lossy hyperspectral image compression using online learning dictionary. Spectral dictionary that ...
In the field of hyper-spectral imaging, the development of efficient compression techniques is critical because datasets containing high-dimensional information ...
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Mar 28, 2019 · Here, we propose a low-complexity compression approach for multispectral images based on convolution neural networks (CNNs) with NTD.
In this work, we consider the encoding of multispectral observations into high-order tensor structures which can naturally capture multi-dimensional ...