HIERARCHICAL DATA ORGANIZATION FOR DENSE OPTICAL FLOW PROCESSING IN A COMPUTER VISION SYSTEM

    公开(公告)号:US20210049368A1

    公开(公告)日:2021-02-18

    申请号:US17086560

    申请日:2020-11-02

    Abstract: A computer vision system is provided that includes an image generation device configured to capture consecutive two dimensional (2D) images of a scene, a first memory configured to store the consecutive 2D images, a second memory configured to store a growing window of consecutive rows of a reference image and a growing window of consecutive rows of a current image, wherein the reference image and the current image are a pair of consecutive 2D images stored in the first memory, a third memory configured to store a sliding window of pixels fetched from the growing window of the reference image, wherein the pixels in the sliding window are stored in tiles, and a dense optical flow engine (DOFE) configured to determine a dense optical flow map for the pair of consecutive 2D images, wherein the DOFE uses the sliding window as a search window for pixel correspondence searches.

    Down Scaling Images in a Computer Vision System

    公开(公告)号:US20200349671A1

    公开(公告)日:2020-11-05

    申请号:US16930543

    申请日:2020-07-16

    Abstract: An apparatus for scaling images is provided that includes at least two input ports, a scaling component coupled to the at least two input ports, the scaling component including a plurality of scalers, the scaling component configurable to map any scaler to any input port of the at least two input ports and configurable to map more than one scaler to any input port, and a memory coupled to the at least two input ports and to outputs of the plurality of scalers, the memory configured to store image data for each input port and scaled image data output by the plurality of scalers.

    Universal and adaptive de-mosaicing (CFA) system

    公开(公告)号:US10735700B2

    公开(公告)日:2020-08-04

    申请号:US16438876

    申请日:2019-06-12

    Abstract: A method of de-mosaicing pixel data from an image processor includes generating a pixel block that includes a plurality of image pixels. The method also includes determining a first image gradient between a first set of pixels of the pixel block and a second image gradient between a second set of pixels of the pixel block. The method also includes determining a first adaptive threshold value based on intensity of a third set of pixels of the pixel block. The pixels of the third set of pixels are adjacent to one another. The method also includes filtering the pixel block in a vertical, horizontal, or neutral direction based on the first and second image gradients and the first adaptive threshold value utilizing a plurality of FIR filters to generate a plurality of component images.

    DENSE OPTICAL FLOW PROCESSING IN A COMPUTER VISION SYSTEM

    公开(公告)号:US20200027219A1

    公开(公告)日:2020-01-23

    申请号:US16585333

    申请日:2019-09-27

    Abstract: A computer vision system is provided that includes an image generation device configured to generate consecutive two dimensional (2D) images of a scene, and a dense optical flow engine (DOFE) configured to determine a dense optical flow map for pairs of the consecutive 2D images, wherein, for a pair of consecutive 2D images, the DOFE is configured to perform a predictor based correspondence search for each paxel in a current image of the pair of consecutive 2D images, wherein, for an anchor pixel in each paxel, the predictor based correspondence search evaluates a plurality of predictors to select a best matching pixel in a reference image of the pair of consecutive 2D images, and determine optical flow vectors for each pixel in a paxel based on the best matching pixel selected for the anchor pixel of the paxel.

    METHOD AND APPARATUS OF HEVC DE-BLOCKING FILTER

    公开(公告)号:US20190394472A1

    公开(公告)日:2019-12-26

    申请号:US16564871

    申请日:2019-09-09

    Abstract: A method of de-blocking filtering a processed video is provided. The processed video includes a plurality of blocks and each block includes a plurality of sub-blocks. A current block of the plurality of blocks includes vertical edges and horizontal edges. The processed video further includes a set of control parameters and reconstructed pixels corresponding to the current block. A boundary strength index is estimated at the vertical edges and at the horizontal edges of the current block. The set of control parameters, the reconstructed pixels corresponding to the current block and partially filtered pixels corresponding to a set of adjacent sub-blocks are loaded. The vertical edges and the horizontal edges of the current block are filtered based on the boundary strength index and the set of control parameters such that a vertical edge of the current block is filtered before filtering at least one horizontal edge of the current block.

    UNIVERSAL AND ADAPTIVE DE-MOSAICING (CFA) SYSTEM

    公开(公告)号:US20190295220A1

    公开(公告)日:2019-09-26

    申请号:US16438876

    申请日:2019-06-12

    Abstract: A method of de-mosaicing pixel data from an image processor includes generating a pixel block that includes a plurality of image pixels. The method also includes determining a first image gradient between a first set of pixels of the pixel block and a second image gradient between a second set of pixels of the pixel block. The method also includes determining a first adaptive threshold value based on intensity of a third set of pixels of the pixel block. The pixels of the third set of pixels are adjacent to one another. The method also includes filtering the pixel block in a vertical, horizontal, or neutral direction based on the first and second image gradients and the first adaptive threshold value utilizing a plurality of FIR filters to generate a plurality of component images.

    METHOD AND APPARATUS FOR REAL-TIME SAO PARAMETER ESTIMATION

    公开(公告)号:US20190289297A1

    公开(公告)日:2019-09-19

    申请号:US16432453

    申请日:2019-06-05

    Abstract: The disclosure provides a sample adaptive offset (SAO) encoder. The SAO encoder includes a statistics collection (SC) block and a rate distortion optimization (RDO) block coupled to the SC block. The SC block receives a set of deblocked pixels and a set of original pixels. The SC block categorizes each deblocked pixel of the set of deblocked pixels in at least one of a plurality of band and edge categories. The SC block estimates an error in each category as difference between a deblocked pixel of the set of deblocked pixels and corresponding original pixel of the set of original pixels. The RDO block determines a set of candidate offsets associated with each category and selects a candidate offset with a minimum RD cost. The minimum RD cost is used by a SAO type block and a decision block to generate final offsets for the SAO encoder.

    Method and apparatus for real-time SAO parameter estimation

    公开(公告)号:US10321135B2

    公开(公告)日:2019-06-11

    申请号:US15970497

    申请日:2018-05-03

    Abstract: The disclosure provides a sample adaptive offset (SAO) encoder. The SAO encoder includes a statistics collection (SC) block and a rate distortion optimization (RDO) block coupled to the SC block. The SC block receives a set of deblocked pixels and a set of original pixels. The SC block categorizes each deblocked pixel of the set of deblocked pixels in at least one of a plurality of band and edge categories. The SC block estimates an error in each category as difference between a deblocked pixel of the set of deblocked pixels and corresponding original pixel of the set of original pixels. The RDO block determines a set of candidate offsets associated with each category and selects a candidate offset with a minimum RD cost. The minimum RD cost is used by a SAO type block and a decision block to generate final offsets for the SAO encoder.

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