title: Compressive spectral imaging using variable number of measurements.
abstract: The compressive spectral imaging method always cuts down on the number of images for obtaining the spectral data cube of a scene. Our method cuts down on the number of sensors on the imaging plane, so as to fit some practical constraints, (e.g., size, weight, battery capacity, memory space, transmission bandwidth). Moreover, only a few of sensors on the imaging plane are needed, while more prior knowledge about the object in the scene has been achieved. The proposed method is based on the concept of coded dispersion, by which many pixels of spectral data are caught by one pixel on the imaging plane. Its measurement matrix is modified so that the number of measurements can be variable under different circumstances to save the transmission bandwidth. We demonstrate the validity of the proposed method, that with prior knowledge of scenes available, it offers a way to acquire spectral images using a variable number of measurements.
authors.forename: Yaohai
authors.initials: Y
authors.lastname: Lin
authors.forename: Xuemei
authors.initials: X
authors.lastname: Xie
authors.forename: Guangming
authors.initials: G
authors.lastname: Shi
authors.forename: Danhua
authors.initials: D
authors.lastname: Liu
authors.forename: Dahua
authors.initials: D
authors.lastname: Gao