R
Ran Tao
Researcher at Beijing Institute of Technology
Publications - 333
Citations - 7170
Ran Tao is an academic researcher from Beijing Institute of Technology. The author has contributed to research in topics: Fractional Fourier transform & Fourier transform. The author has an hindex of 34, co-authored 310 publications receiving 4778 citations. Previous affiliations of Ran Tao include Temple University & University of Iceland.
Papers
More filters
Journal ArticleDOI
Double image encryption based on random phase encoding in the fractional Fourier domain
TL;DR: A novel image encryption method is proposed by utilizing random phase encoding in the fractional Fourier domain to encrypt two images into one encrypted image with stationary white distribution that can be recovered without cross-talk.
Journal ArticleDOI
Short-Time Fractional Fourier Transform and Its Applications
Ran Tao,Yan-Lei Li,Yue Wang +2 more
TL;DR: The short-time fractional Fourier transform (STFRFT) is proposed to solve the problem of locating the fractional fourier domain (FRFD)-frequency contents which is required in some applications and its inverse transform, properties and computational complexity are presented.
Journal ArticleDOI
Detection and parameter estimation of multicomponent LFM signal based on the fractional Fourier transform
TL;DR: A signal separation technique in the fractional Fourier domain is proposed which can effectively suppress the interferences on the detection of the weak components brought by the stronger components.
Journal ArticleDOI
Research progress of the fractional Fourier transform in signal processing
Ran Tao,Bing Deng,Yue Wang +2 more
TL;DR: The fractional Fourier transform has been comprehensively and systematically treated from the signal processing point of view and a course from the definition to the applications is provided, especially as a reference and an introduction for researchers and interested readers.
Journal ArticleDOI
ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features
TL;DR: In this paper, the authors proposed a novel object detection framework, called Optical Remote Sensing Imagery detector (ORSIm detector), integrating diverse channel features extraction, feature learning, fast image pyramid matching, and boosting strategy.