Texas Instruments Corporation

Shashank Dabral

Mihir Narendra Mody

Niraj Nandan

Rajasekhar Reddy Allu

Gang Hua

Mayank Mangla

Hetul Sanghvi

Vikram Vijayanbabu Appia

Aishwarya Dubey

Brian Okchon Chae

Sujith Shivalingappa

Denis R Beaudoin

Martin Fritz Mueller

Hemant Hariyani

Veeramanikandan Raju

Brijesh Rameshbhai Jadav

William Cronin Wallace

Anthony J Lell

Jesse Gregory Villarreal, Jr

Peter Labaziewicz

Vikram VijayanBabu Appia

Lucas Carl Weaver

Hamid Rahim Sheikh

Jeffrey Matthew Kempf

Zhongyan Sheng

Rajat Sagar

John Peter Fenske

Denis Roland Beaudoin

Ganapathy Sivakumar

Frederic Jean Noraz

Gavin Camillo Perrella

Stephen Busch

Brijesh Rameshbhal Jadav

Jaime Rene De La Cruz Vasquez

Gowtham Abhilash Tammana

Rajashekhar Allu

Mohhamad Jacob Pulliam

Akeem Whitehead

A method for processing RGB-Infrared (RGB-IR) sensor data is provided that includes receiving a raw RGB-IR image, determining whether to process the raw RGB-IR image in day mode or night mode, generating, when day mode is determined, an infrared (IR) subtracted raw Bayer image from the raw RGB-IR image and processing the IR subtracted raw Bayer image in an image signal processor (ISP), and generating, when night mode is determined, an IR image from the raw RGB-IR image.

Method and apparatus for processing RGB-infrared (RGB-IR) sensor data

In some examples, a method comprises receiving pixel data from an image capture device having a color filter, wherein the pixel data represents a portion of an image. The method further includes performing wavelet decomposition on the pixel data to produce decomposed pixel data and determining a local intensity of the pixel data. The method also includes determining a noise threshold value based on the local intensity and a noise intensity function that is based on the color filter; determining a noise value for the pixel data based on the decomposed pixel data and the noise threshold value; and correcting the pixel data based on the noise value to produce an output image.

Noise estimation using user-configurable information

A technique for image processing, comprising: receiving input image data, wherein the image data is companded into a first bit depth, wherein the image data includes incomplete color values for pixels of the image data, and wherein the image data is associated with a first color space, interpolating the image data to generate color values for the incomplete color values for pixels of the image data, expanding the image data from the first bit depth to a second bit depth, wherein the color values of the expanded image data have a linear dynamic range, and wherein the second bit depth is higher than the first bit depth, converting the color values for pixels of the expanded image data from the first color space to a second color space, and compressing the color values for pixels of the image data to a third bit depth, the third bit depth lower than the second bit depth, and wherein the compressed color values have a nonlinear dynamic range.

High precision color processing for wide dynamic range sensors

Local automatic white balance (AWB) of wide dynamic range (WDR) images is provided. Methods and systems include collecting, by an image signal processor (ISP), statistics for local AWB from at least one wide dynamic range (WDR) image received by the ISP; generating, by a processor, based on the statistics, local gain lookup tables (LUTs), one for each color channel represented in the WDR image(s), each local gain LUT providing a correlation between gain and intensity; and storing the local gain LUTs. Further processing includes, for each of multiple pixels of a WDR image to be output calculating an intensity value, accessing the local gain LUT for the color channel corresponding to that pixel using the calculated intensity value to identify a corresponding local gain value, and applying the local gain value to that pixel.

Intensity separated local white balance correction

Techniques for image processing including receiving input image data, wherein the input image data includes data associated with a clear color channel, receiving a color offset value associated with a color channel, wherein color values for the color channel are not provided in the input image data, based on the color offset value, generating intermediate estimated color values for the color channel, wherein generating the intermediate estimated color values includes: clipping color values that have a magnitude greater than the color offset value, and adjusting color values that have a magnitude less than the color offset value based on the color offset value, applying a color correction function to the intermediate estimated color values based on the color offset value to determine color corrected estimated color values, and outputting the color corrected estimated color values.

Suppression of clipping artifacts from color conversion

A technique including capturing, by one or more cameras of a set of cameras disposed about a vehicle, one or more images, wherein a surround view system of the vehicle is configured to render a surround view image using a first hardware accelerator based on the one or more images, determining that a first hardware accelerator is unavailable, and rendering the surround view image using a second hardware accelerator based on the captured one or more images.

Fail safe surround view

A method for geometrically correcting a distorted input frame and generating an undistorted output frame includes capturing and storing an input frame in an external memory, allocating an output frame with an output frame size and dividing the output frame into output blocks, computing a size of the input blocks in the input image corresponding to each output blocks, checking if the size of the input blocks is less than the size of the internal memory and if not dividing until the required input block size of divided sub blocks is less than the size of the internal memory, programming an apparatus with input parameters, fetching the input blocks into an internal memory, processing each of the divided sub blocks sequentially and processing the next output block in step until all the output blocks are processed; and composing the output frame for each of the blocks in the output frame.

Method and apparatus for dynamic block partition of an image

Methods and integrated circuits to process image data from single or multiple digital overlap (DOL) wide dynamic range (WDR) sensors, in which first received pixel data associated with a first exposure of a sensor image is stored in a DDR memory circuit, second received pixel data associated with a second exposure of the image is stored in the first buffer, third received pixel data associated with a third exposure of the image is stored in a second buffer, and fourth received pixel data associated with a fourth exposure of the image is provided to a merge circuit, and merged pixel data is stored in a dynamically partitioned line buffer for processing by an image pipeline circuit to facilitate interfacing multiple DOL WDR sensors in an interleaved fashion.

Image data processing for digital overlap wide dynamic range sensors

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.

Universal and adaptive de-mosaicing (CFA) system

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.

Method and apparatus for arbitrary output shape processing of an image

Frames from an image stream or streams are processed by independently operating digital signal processors (DSPs), with only frame checking microprocessors operating in a lockstep mode. In one example, two DSP are operating on alternate frames. Each DSP processes the frames and produces prediction values for the next frame. The lockstep microprocessors develop their own next frame prediction. The lockstep processors compare issued frames and previously developed predicted frames for consistency. If the predictions are close enough, the issued frame passes the test. The lockstep processors then compare the issued frame to the preceding two frames for a similar consistency check. If the prior frames are also close enough, the issued frame is acceptable. In another example, hardware checkers are provided to compare the present frame with a larger number of prior frames. The hardware checkers provide comparison results to the lockstep processors to compare against allowable variation limits.

Alternating frame processing operation with predicted frame comparisons for high safety level use

A system on a chip (SoC) includes a digital signal processor (DSP) and a graphics processing unit (GPU) coupled to the DSP. The DSP is configured to receive a stream of received depth measurements and generate a virtual bowl surface based on the stream of received depth measurements. The DSP is also configured to generate a bowl to physical camera mapping based on the virtual bowl surface. The GPU is configured to receive a first texture and receive a second texture. The GPU is also configured to perform physical camera to virtual camera transformation on the first texture and on the second texture, based on the bowl to physical camera mapping, to generate an output image.

Surround view

Method and apparatus for processing RGB-infrared (RGB-IR) sensor

An example includes a system, having: an illumination source configured to produce illumination light; and a spatial light modulator (SLM) optically coupled to the illumination source, the SLM comprising an array of picture elements. The SLM is configured to: receive the illumination light; direct, by a first portion of the picture elements, on state light in a first direction; and direct, by a second portion of the picture elements, off state light in a second direction. The example system includes imaging optics optically coupled to the SLM, the imaging optics configured to receive the on state light from the SLM and to project an image as an image portion of a beam; and non-imaging optics optically coupled to the SLM, the non-imaging optics configured to receive the off state light from the SLM and to project the off state light as part of the beam.

Adaptive light source with spatial light modulator

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.

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Allen, TX, United States of America

Shashank Dabral