Patents by Inventor Han Bin SON

Han Bin SON 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).

  • Patent number: 11670011
    Abstract: An image compression apparatus includes: an image acquisition unit configured to acquire a raw data image; a pre-processing network configured to receive the raw data image and pre-process the raw data image according to a pattern estimation method learned beforehand; and an encoder unit configured to receive the pre-processed image and compress the pre-processed image according to a pre-designated standard compression technique to output a compressed image. The pre-processing network, which can be added during learning and can be implemented as an artificial neural network, can have learned beforehand by way of a backpropagation of a restoration error through a codec modeling unit that has learned beforehand to simulate a standard codec unit, where the restoration error can be obtained by comparing a restored image obtained based on a simulated decoded image with the raw data image.
    Type: Grant
    Filed: January 11, 2021
    Date of Patent: June 6, 2023
    Assignee: INDUSTRY-ACADEMIC COOPERATION FOUNDATION YONSEI UNIVERSITY
    Inventors: Sang Youn Lee, Tae Oh Kim, Han Bin Son, Hyeong Min Lee
  • Publication number: 20220222864
    Abstract: An image compression apparatus includes: an image acquisition unit configured to acquire a raw data image; a pre-processing network configured to receive the raw data image and pre-process the raw data image according to a pattern estimation method learned beforehand; and an encoder unit configured to receive the pre-processed image and compress the pre-processed image according to a pre-designated standard compression technique to output a compressed image. The pre-processing network, which can be added during learning and can be implemented as an artificial neural network, can have learned beforehand by way of a backpropagation of a restoration error through a codec modeling unit that has learned beforehand to simulate a standard codec unit, where the restoration error can be obtained by comparing a restored image obtained based on a simulated decoded image with the raw data image.
    Type: Application
    Filed: January 11, 2021
    Publication date: July 14, 2022
    Inventors: Sang Youn LEE, Tae Oh KIM, Han Bin SON, Hyeong Min LEE