Patents by Inventor Roni Lanzet

Roni Lanzet 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: 8098733
    Abstract: A motion estimator uses many parallel Arithmetic-Logic-Unit (ALU) processors to simultaneously perform searches in many directions from a starting point. Each processor follows a different path outward from the starting point, generating sum-of-absolute differences (SADs) for each point in the path. A best SAD for the path is kept, along with an index into motion vector tables containing X,Y points for all paths. Current and best SAD's, thresholds, and indexes are stored in an ALU dedicated memory. When the number of best SAD's meeting thresholds exceeds a target, the current search-level ends. The index of the overall best SAD locates a new starting point, and a next-denser search-level is performed in the same manner, but over a smaller search area. Each processor calculates SAD's for one 16×16 macroblock, four 8×8 blocks, and 16 4×4 blocks and the net best SAD of these 3 types determines partitioning.
    Type: Grant
    Filed: March 10, 2008
    Date of Patent: January 17, 2012
    Assignee: NeoMagic Corp.
    Inventors: Dmitry Veremeev, Gregory Gordon, Roni Lanzet
  • Publication number: 20090225845
    Abstract: A motion estimator uses many parallel Arithmetic-Logic-Unit (ALU) processors to simultaneously perform searches in many directions from a starting point. Each processor follows a different path outward from the starting point, generating sum-of-absolute differences (SADs) for each point in the path. A best SAD for the path is kept, along with an index into motion vector tables containing X,Y points for all paths. Current and best SAD's, thresholds, and indexes are stored in an ALU dedicated memory. When the number of best SAD's meeting thresholds exceeds a target, the current search-level ends. The index of the overall best SAD locates a new starting point, and a next-denser search-level is performed in the same manner, but over a smaller search area. Each processor calculates SAD's for one 16×16 macroblock, four 8×8 blocks, and 16 4×4 blocks and the net best SAD of these 3 types determines partitioning.
    Type: Application
    Filed: March 10, 2008
    Publication date: September 10, 2009
    Applicant: NEOMAGIC CORP.
    Inventors: Dmitry Veremeev, Gregory Gordon, Roni Lanzet