Night Vision Processing and Understanding

Lianfa Bai: His interests include photoelectron imaging, multispectral imaging, image processing and computer vision, and intelligent applications of spectral imaging. He has also pursued unique research on low level light visible infrared (near-infrared, medium-wave infrared, long-wave infrared) imaging and understanding. He has published more than 130 relevant papers, including in Optics Letters, IEEE Transactions, and PLOS ONE. Jing Han: Her research is mainly based on system imaging characteristics, studying spectral data mining, visual modelling and optimization, and non-training/small sample training classification to improve the computational efficiency and robustness of multidimensional images, and to promote the practicality of multi-source multispectral imaging systems. Jiang Yue: He is currently working on new technologies to boost the SNR of high-dimension data, including acquisition methods, and data denoising algorithms. In particularhe is dealing with two problems: developing high SNR coding snapshot measurements and finding reversible denoising transformations. He and his co-operators have published more than 15 relevant papers, including in Optics Letters, IEEE Transactions on Image Processing, and Applied Physics B.

Introduction.- High Snr Hyperspectral Night Vision Image Acquisition with Multiplexing.- Multi-Visual Task Based on Night Vision Data Structure and Feature Analysis.- Feature Classification Based on Manifold Dimension Reduction for Night Vision Images.- Night Vision Data Classification Based on Sparse Representation and Random Subspace.- Learning Based Night Vision Image Recognition and Object Detection.- Non-Learning Based Motion Cognitive Detection and Self-Adaptable Tracking for Night Vision Videos.- The Colorization of Low Light Level Image Based on the Rule Mining.