Hyperspectral images have huge data volume that contains spectral and spatial information. This high data volume leads to processing, storage, and transmission problems. Moreover, insufficient training data results in ...

The purpose of the paper is to find the best quantizer allocation for compressed-sensed acquired images, by using a graph-cut quantizer allocation method. The compressed sensed acquisition is realized in a block-based ...

The joint estimation of the parameters and the states of the hemodynamic model from the blood oxygen level dependent (BOLD) signal is a challenging problem. In the functional magnetic resonance imaging (fMRI) literature, ...

Sparse coding ensures to express the data in terms of a few nonzero dictionary elements. Since the data size is large for hyperspectral imagery, it is reasonable to use sparse coding for compression of hyperspectral images. ...

In this paper, a flame detection system using a differential Pyro-electric Infrared (PIR) sensor is proposed. A differential PIR sensor is only sensitive to sudden temperature variations within its viewing range and it ...