Abstract: Described examples include an integrated circuit including a vector multiply unit including a plurality of multiply/accumulate nodes, in which the vector multiply unit is operable to provide an output from the multiply/accumulate nodes, a first data feeder operable to provide first data to the vector multiply unit in vector format, and a second data feeder operable to provide second data to the vector multiply unit in vector format.

Abstract: A video hardware engine with multi-threading functionality is disclosed. The video hardware engine includes a video hardware accelerator unit and a controller. The controller is coupled to the video hardware accelerator unit. The controller operates in an encode mode and a decode mode. In the encode mode, the controller receives a plurality of frames and encode attributes associated with each frame of the plurality of frames. The encode attributes associated with a frame of the plurality of frames is processed to generate encode parameters associated with the frame. The video hardware accelerator unit is configured to process the frame based on the encode parameters to generate an output. The output of the video hardware accelerator unit is processed to generate a compressed bit-stream and an encode status. In decode mode, the controller receives a compressed bit-stream and decode attributes and generates a plurality of frames and a decode status.

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.

Abstract: A reconfigurable image processing pipeline includes an image signal processor (ISP), a control processor, and a local memory. ISP processes raw pixel data for a frame based on an image processing parameter and provides lines of processed pixel data to control processor via a first interface. For each region of interest (ROI) in the frame, ISP generates auto-exposure and auto-white balance (2A) statistics based on the lines for the ROI and writes them to the local memory via a second interface. Control processor reads 2A statistics from the local memory, determines the image processing parameter based on them, and provides the image processing parameter to ISP. ISP also generates an integer N bin histogram for control processor, which sums a portion of the N total bins and compares the summed bin count to a lighting transition threshold. The image processing parameter is further based on the comparison.

Abstract: A lens distortion correction function operates by backmapping output images to the uncorrected, distorted input images. As a vision image processor completes processing on the image data lines needed for the lens distortion correction function to operate on a group of output, undistorted image lines, the lens distortion correction function begins processing the image data. This improves image processing pipeline delays by overlapping the operations. The vision image processor provides output image data to a circular buffer in SRAM, rather than providing it to DRAM. The lens distortion correction function operates from the image data in the circular buffer. By operating from the SRAM circular buffer, access to the DRAM for the highly fragmented backmapping image data read operations is removed, improving available DRAM bandwidth. By using a circular buffer, less space is needed in the SRAM. The improved memory operations further improve the image processing pipeline delays.

Abstract: An image signal processor includes a first matrix processing circuit, a post processing circuit, a second matrix processing circuit, and a split visual and analytics circuit. The first matrix processing circuit is configured to receive a plurality of component images generated based on an image captured by an image sensor and generate a plurality of first matrix outputs based on the plurality of component images. The post processing circuit is configured to perform color conversion on the plurality of first matrix outputs to generate a first luminance component of the image and a chrominance component of the image. The second matrix processing circuit is configured to perform color conversion on the plurality of first matrix outputs to generate a second luminance component of the image and a saturation component of the image. The split visual and analytics circuit is configured to generate visual and analytic data of the image.

Abstract: A video hardware engine with multi-threading functionality is disclosed. The video hardware engine includes a video hardware accelerator unit and a controller. The controller is coupled to the video hardware accelerator unit. The controller operates in an encode mode and a decode mode. In the encode mode, the controller receives a plurality of frames and encode attributes associated with each frame of the plurality of frames. The encode attributes associated with a frame of the plurality of frames is processed to generate encode parameters associated with the frame. The video hardware accelerator unit is configured to process the frame based on the encode parameters to generate an output. The output of the video hardware accelerator unit is processed to generate a compressed bit-stream and an encode status. In decode mode, the controller receives a compressed bit-stream and decode attributes and generates a plurality of frames and a decode status.

Abstract: Methods, apparatus, and articles of manufacture providing an efficient safety mechanism for signal processing hardware are disclosed. An example apparatus includes an input interface to receive an input signal; a hardware accelerator to process the input signal, the hardware accelerator including: unprotected memory to store non-critical data corresponding to the input signal; and protected memory to store critical data corresponding to the input signal; and an output interface to transmit the processed input signal.

Abstract: An apparatus and method for geometrically correcting an arbitrary shaped input frame and generating an undistorted output frame. The method includes capturing arbitrary shaped input images with multiple optical devices and processing the images, identifying redundant blocks and valid blocks in each of the images, allocating an output frame with an output frame size and dividing the output frame into regions shaped as a rectangle, programming the apparatus and disabling processing for invalid blocks in each of the regions, fetching data corresponding to each of the valid blocks and storing in an internal memory, interpolating data for each of the regions with stitching and composing the valid blocks for the output frame and displaying the output frame on a display module.

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.

Abstract: A lens distortion correction function operates by backmapping output images to the uncorrected, distorted input images. As a vision image processor completes processing on the image data lines needed for the lens distortion correction function to operate on a group of output, undistorted image lines, the lens distortion correction function begins processing the image data. This improves image processing pipeline delays by overlapping the operations. The vision image processor provides output image data to a circular buffer in SRAM, rather than providing it to DRAM. The lens distortion correction function operates from the image data in the circular buffer. By operating from the SRAM circular buffer, access to the DRAM for the highly fragmented backmapping image data read operations is removed, improving available DRAM bandwidth. By using a circular buffer, less space is needed in the SRAM. The improved memory operations further improve the image processing pipeline delays.

Abstract: An image signal processor includes a first matrix processing circuit, a post processing circuit, a second matrix processing circuit, and a split visual and analytics circuit. The first matrix processing circuit is configured to receive a plurality of component images generated based on an image captured by an image sensor and generate a plurality of first matrix outputs based on the plurality of component images. The post processing circuit is configured to perform color conversion on the plurality of first matrix outputs to generate a first luminance component of the image and a chrominance component of the image. The second matrix processing circuit is configured to perform color conversion on the plurality of first matrix outputs to generate a second luminance component of the image and a saturation component of the image. The split visual and analytics circuit is configured to generate visual and analytic data of the image.

Abstract: A video decoder system, in one embodiment, includes one or more processors and a memory storing instructions that when executed by the one or more processors cause the video decoding system to perform an entropy decoding operation in a frame level pipelined manner on a bitstream representative of encoded video data to produce first output data, perform at least one of an inverse quantization operation or an inverse frequency transform operation in a row level pipelined manner on the first output data to produce second output data, perform a deblocking filtering operation on first input data that includes the second output data in a row level pipelined manner to produce third output data, and output a decoded video output based on the third output data.

Abstract: Methods, apparatus, and articles of manufacture providing an efficient safety mechanism for signal processing hardware are disclosed. An example apparatus includes an input interface to receive an input signal; a hardware accelerator to process the input signal, the hardware accelerator including: unprotected memory to store non-critical data corresponding to the input signal; and protected memory to store critical data corresponding to the input signal; and an output interface to transmit the processed input signal.

Abstract: An integrated circuit includes: a local memory; and a first processing circuit coupled to the local memory. The first processing component is configured to: receive a first set of image data; perform a first image processing operation on the first set of image data to produce a second set of image data; and store at least some of the second set of image data into the local memory. The integrated circuit also includes a second processing circuit coupled to the local memory and configured to: receive at least some of the second set of image data from the local memory; and perform a second image processing operation on the second set of image data to produce a third set of image data.

Abstract: An apparatus and method for geometrically correcting an arbitrary shaped input frame and generating an undistorted output frame. The method includes capturing arbitrary shaped input images with multiple optical devices and processing the images, identifying redundant blocks and valid blocks in each of the images, allocating an output frame with an output frame size and dividing the output frame into regions shaped as a rectangle, programming the apparatus and disabling processing for invalid blocks in each of the regions, fetching data corresponding to each of the valid blocks and storing in an internal memory, interpolating data for each of the regions with stitching and composing the valid blocks for the output frame and displaying the output frame on a display module.

Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to implement thread scheduling for multithreaded data processing environments are disclosed. Example thread schedulers disclosed herein for a data processing system include a buffer manager to determine availability of respective buffers to be acquired for respective processing threads implementing respective functional nodes of a processing flow, and to identify first ones of the processing threads as stalled due to unavailability of at least one buffer in the respective buffers to be acquired for the first ones of the processing threads. Disclosed example thread schedulers also include a thread execution manager to initiate execution of second ones of the processing threads that are not identified as stalled.

Abstract: A hub that receives sensor data streams and then distributes the data streams to the various systems that use the sensor data. A demultiplexer (demux) receives the streams, filters out undesired streams and provides desired streams to the proper multiplexer (mux) or muxes of a series of muxes. Each mux combines received streams and provides an output stream to a respective formatter or output block. The formatter or output block is configured based on the destination of the mux output stream, such as an image signal processor, a processor, memory or external transmission. The output block reformats the received stream to a format appropriate for the recipient and then provides the reformatted stream to that recipient.

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.

Abstract: A video decoder system, in one embodiment, includes one or more processors and a memory storing instructions that when executed by the one or more processors cause the video decoding system to perform an entropy decoding operation in a frame level pipelined manner on a bitstream representative of encoded video data to produce first output data, perform at least one of an inverse quantization operation or an inverse frequency transform operation in a row level pipelined manner on the first output data to produce second output data, perform a deblocking filtering operation on first input data that includes the second output data in a row level pipelined manner to produce third output data, and output a decoded video output based on the third output data.