Veoneer Sweden Ab

Arriver Software Ab

Qualcomm Auto Ltd.

Leif Lindgren

Per Knutsson

Fredrik Medley

Henrik Eliasson

This disclosure provides systems, methods, and devices for vehicle driving assistance systems that support image processing for vehicular monitoring operations. In a first aspect, a method of image processing includes receiving image data from an image sensor comprising a red-clear-clear-green (RCCG) color filter, wherein the image data comprises a first channel corresponding to red, a second channel corresponding to clear, and a third channel corresponding to green, wherein the image data is in a logarithmic domain; and processing the image data by performing operations including linearization, tone mapping, demosaicing, and color mapping. Other aspects and features are also claimed and described.

Image sensor with red-clear-clear-green (RCCG) color filter array (CFA) for vehicle sensing applications

A vision system () for a motor vehicle includes a stereo imaging apparatus () adapted to capture images from a surrounding of the motor vehicle, a disparity calculation block () adapted to calculate a stereo disparity of left/right images captured by the stereo imaging apparatus (), and a processing device () adapted to perform image processing of images captured by the imaging apparatus (). The vision system is adapted to perform time sharing of the disparity calculation block () between the stereo disparity calculation and calculation of a one-dimensional optical flow of captured images in a horizontal direction only.

Vision system and method for a motor vehicle

A vision system () for a motor vehicle with a stereo imaging apparatus () with imaging devices () adapted to capture images from a surrounding of the motor vehicle, and a processing device () adapted to process images captured by the imaging devices () and to detect objects, and track detected objects over several time frames, in the captured images. The processing device () is adapted to obtain an estimated value for the intrinsic yaw error of the imaging devices () by solving a set of equations, belonging to one particular detected object (), using a non-linear equation solver method, where each equation corresponds to one time frame and relates a frame time, a disparity value of the particular detected object, an intrinsic yaw error and a kinematic variable of the vehicle.

A motor vehicle vision system () including a stereo imaging system () and a data processing device () establishing an object detector () to detect an object and a tracker (). The data processing device () calculates a size related value and a disparity related value for the object. An analysis section () performs an analysis on a group of at least five data points corresponding to different times, each data point includes a size related value and a disparity related value. The analysis uses predetermined regression function having at least one variable, and yields a best value for each variable corresponding to a best match of the regression function to the data points. The analysis section () calculates from a best value a systematic error in the disparity related values and/or in the size related values.

Vision system for a motor vehicle and method of controlling a vision system

A motor vehicle vision system () includes a pair of imaging devices () forming a stereo imaging apparatus () and a data processing apparatus () for rectification of images captured by the stereo imaging apparatus (), matching of rectified images, and to detect an object in the surrounding of the motor vehicle. The data processing device () performs, for image elements () of a rectified image from one imaging device, a search for a best-matching image element (') in the corresponding rectified image from the other imaging device. The search yielding vertical shift information from which a vertical shift from the image element () to the best-matching image element (&#x2032;) is derivable. The data processing device () calculates a pitch angle error and/or a roll angle error of or between the imaging devices () from the vertical shift information.

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Linköping, Sweden

Leif Lindgren