Patents by Inventor Runqing Liang

Runqing Liang has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Method and system for image reconstruction using target attribute assisted compressive sensing
    Patent number: 10706593
    Abstract: The present invention provides a method for image reconstruction using target attribute assisted compressive sensing, including an initializing step, a subspace partitioning step, an atom set updating step, a sparse coefficient updating step and an outputting step. The present invention further provides a system for image reconstruction using target attribute assisted compressive sensing. A technical scheme provided by the present invention will introduce auxiliary information capable of reflecting target features into subspace partitioning in a case of unknown sparseness of a small target image signal, thereby accurately and effectively selecting the most closely matching dictionary subspace, and realizing efficient and rapid reconstruction of the small target image signal.
    Type: Grant
    Filed: September 4, 2018
    Date of Patent: July 7, 2020
    Assignee: SHENZHEN UNIVERSITY
    Inventors: Jianjun Huang, Runqing Liang, Li Kang, Zhongyin Liang
  • Infrared image reconstruction method based on block-sparse compressive sensing and system thereof
    Patent number: 10412324
    Abstract: The present invention provides an infrared image reconstruction method based on block-sparse compressive sensing. The method includes: a block-sparse representation step: representing consecutive infrared small target image sequences as signals having block-sparse characteristics; a temporal correlation modeling step: modeling a temporal correlation of data between the consecutive infrared small target image sequences under a Bayesian framework; and a signal reconstruction and output step: reconstructing infrared small target images using a sparse learning algorithm and outputting final estimates of the signals. The present invention further provides an infrared image reconstruction system based on block-sparse compressive sensing.
    Type: Grant
    Filed: March 7, 2018
    Date of Patent: September 10, 2019
    Assignee: SHENZHEN UNIVERSITY
    Inventors: Li Kang, Runqing Liang, Jianjun Huang, Jingxiong Huang
  • METHOD AND SYSTEM FOR IMAGE RECONSTRUCTION USING TARGET ATTRIBUTE ASSISTED COMPRESSIVE SENSING
    Publication number: 20180374243
    Abstract: The present invention provides a method for image reconstruction using target attribute assisted compressive sensing, including an initializing step, a subspace partitioning step, an atom set updating step, a sparse coefficient updating step and an outputting step. The present invention further provides a system for image reconstruction using target attribute assisted compressive sensing. A technical scheme provided by the present invention will introduce auxiliary information capable of reflecting target features into subspace partitioning in a case of unknown sparseness of a small target image signal, thereby accurately and effectively selecting the most closely matching dictionary subspace, and realizing efficient and rapid reconstruction of the small target image signal.
    Type: Application
    Filed: September 4, 2018
    Publication date: December 27, 2018
    Inventors: Jianjun Huang, Runqing Liang, Li Kang, Zhongyin Liang
  • INFRARED IMAGE RECONSTRUCTION METHOD BASED ON BLOCK-SPARSE COMPRESSIVE SENSING AND SYSTEM THEREOF
    Publication number: 20180198992
    Abstract: The present invention provides an infrared image reconstruction method based on block-sparse compressive sensing. The method includes: a block-sparse representation step: representing consecutive infrared small target image sequences as signals having block-sparse characteristics; a temporal correlation modeling step: modeling a temporal correlation of data between the consecutive infrared small target image sequences under a Bayesian framework; and a signal reconstruction and output step: reconstructing infrared small target images using a sparse learning algorithm and outputting final estimates of the signals. The present invention further provides an infrared image reconstruction system based on block-sparse compressive sensing.
    Type: Application
    Filed: March 7, 2018
    Publication date: July 12, 2018
    Inventors: Li Kang, Runqing Liang, Jianjun Huang, Jingxiong Huang