High-Dimensional and Low-Quality Visual Information Processing: From Structured Sensing and Understanding (Springer Theses)
暫譯: 高維度與低品質視覺資訊處理：從結構化感知與理解出發（Springer 論文集）

This thesis primarily focuses on how to carry out intelligent sensing and understand the high-dimensional and low-quality visual information. After exploring the inherent structures of the visual data, it proposes a number of computational models covering an extensive range of mathematical topics, including compressive sensing, graph theory, probabilistic learning and information theory. These computational models are also applied to address a number of real-world problems including biometric recognition, stereo signal reconstruction, natural scene parsing, and SAR image processing.