Abstract: Systems, methods, and apparatus are provided for real-time adjustment of image quality parameters. The system includes a controller configured to: acquire an image frame, having a fixed-pixel region that defines a region-of-interest, from one or more imaging devices; apply image processing techniques to determine a modified fixed-pixel region that excludes non-relevant object pixels; alter one or more image quality parameters based on statistics of pixels in the modified fixed-pixel region; and provide the altered one or more image quality parameters to the one or more imaging devices for use with subsequent image frames; wherein the one or more imaging devices produce an image that is tuned, based on the altered one or more image quality parameters, to the portions of the image in the region-of-interest that does not include the non-relevant object pixels.

Abstract: Vision sensor systems and methods detect banding and flicker. The method includes receiving camera data and identifying a light source location in a frame of camera data and assigning a luminance measure at the light source as a signal reference. A region of interest (ROI) is then associated with the light source. The frame is incremented, and then a signal to noise ratio (SNR) at the light source is calculated. A number, N of frames may be processed to identify banding when it is present, and to identify flicker when it is present. Responsive to identifying banding or identifying flicker, a response for a display system or for a machine vision system is generated.

Abstract: Methods and apparatus are provided for real time video upscaling in a vehicle display system. The apparatus includes a camera for capturing an image having a first resolution, a display operative at a second resolution, a sensor for detecting a condition, and a processor for selecting a scaling algorithm in response to the first resolution, the second resolution and the condition, the processor further operative to scale the image from the first resolution to the second resolution to generate a rescaled image and for coupling the rescaled image to the display.

Abstract: In various embodiments, methods, systems, and vehicles are provided for distance determinations using cameras from different vehicles. The system includes a first camera onboard a first vehicle, providing a first image, the first image having therein an object of interest (OOI) for which a distance from the first vehicle is desired; and a second camera, providing second camera data including a second image having therein the OOI. The system further includes a control module configured to process and time synchronize first camera data and second camera data to generate a distance determination for the OOI, using the first camera data, the second camera data, and a distance between the first and second camera.

Abstract: In various embodiments, methods, systems, and vehicles are provided that include obtaining first camera images from a first camera onboard a first vehicle; generating, via one or more computer processors, a first situation awareness graph with respect to objects near the first vehicle, using the first camera images; obtaining second camera images from a second camera of a second device that is in proximity to the first vehicle; generating, via one or more computer processors, a second situation awareness graph with the respect to the objects, using the second camera images; and generating, via one or more computer processor, a global situation awareness graph with respect to the objects, by merging the first situation awareness graph with the second situation awareness graph, using respective first and second weights for the first and second situation awareness graphs.

Abstract: Methods and systems are provided for controlling camera images for a camera of a vehicle are provided. In certain examples, a vehicle includes a camera, an input unit, and a processor. The input unit is configured to obtain data pertaining to a light pattern in proximity to the vehicle. The processor is configured to at least facilitate: (i) determining the light pattern in proximity to the vehicle using the data; and (ii) providing instructions for selectively binning the camera images based on the light pattern, the selectively binning including binning first pixels together for a particular image or portion thereof, but leaving second pixels for the particular image un-binned, based on the light pattern.

Abstract: A method and system to perform dynamic demosaicing for a camera in a vehicle involve an array of image sensors of the camera to obtain light intensity values. Each image sensor of the array of image sensors represents a pixel. An array of filters of the camera overlays the array of image sensors and restricts a wavelength range for which the one image sensor of the array of image sensors obtains the light intensity value. The array of filters includes at least two different types of filters corresponding with two different wavelength ranges. A processor estimates a current state associated with the vehicle and selects a demosaicing algorithm based on the current state such that, for each pixel, the demosaicing algorithm facilitates an estimate of the light intensity value at a different wavelength range than the wavelength range for which the corresponding image sensor obtained the light intensity value.

Abstract: In various embodiments, methods, systems, and vehicles are provided for distance determinations using cameras from different vehicles. The system includes a first camera onboard a first vehicle, providing a first image, the first image having therein an object of interest (OOI) for which a distance from the first vehicle is desired; and a second camera, providing second camera data including a second image having therein the OOI. The system further includes a control module configured to process and time synchronize first camera data and second camera data to generate a distance determination for the OOI, using the first camera data, the second camera data, and a distance between the first and second camera.

Abstract: In various embodiments, methods, systems, and vehicles are provided that include obtaining first camera images from a first camera onboard a first vehicle; generating, via one or more computer processors, a first situation awareness graph with respect to objects near the first vehicle, using the first camera images; obtaining second camera images from a second camera of a second device that is in proximity to the first vehicle; generating, via one or more computer processors, a second situation awareness graph with the respect to the objects, using the second camera images; and generating, via one or more computer processor, a global situation awareness graph with respect to the objects, by merging the first situation awareness graph with the second situation awareness graph, using respective first and second weights for the first and second situation awareness graphs.

Abstract: A method and system to perform dynamic demosaicing for a camera in a vehicle involve an array of image sensors of the camera to obtain light intensity values. Each image sensor of the array of image sensors represents a pixel. An array of filters of the camera overlays the array of image sensors and restricts a wavelength range for which the one image sensor of the array of image sensors obtains the light intensity value. The array of filters includes at least two different types of filters corresponding with two different wavelength ranges. A processor estimates a current state associated with the vehicle and selects a demosaicing algorithm based on the current state such that, for each pixel, the demosaicing algorithm facilitates an estimate of the light intensity value at a different wavelength range than the wavelength range for which the corresponding image sensor obtained the light intensity value.

Abstract: One general aspect includes a method of sound masking, the method including: receiving, via a processor, a privacy request from a user; generating, via the processor, a masking sound configured to mask speech of the user in response to the privacy request; and providing, via the processor, the masking sound as an audio output through an audio system.

Abstract: Methods and systems are provided for controlling camera images for a camera of a vehicle are provided. In certain examples, a vehicle includes a camera, an input unit, and a processor. The input unit is configured to obtain data pertaining to a light pattern in proximity to the vehicle. The processor is configured to at least facilitate: (i) determining the light pattern in proximity to the vehicle using the data; and (ii) providing instructions for selectively binning the camera images based on the light pattern, the selectively binning including binning first pixels together for a particular image or portion thereof, but leaving second pixels for the particular image un-binned, based on the light pattern.

Abstract: A vehicular interior lighting system features a lamp assembly having two input terminals, each connected to a power source via two control switches. The lamp assembly further includes a lighting element connected at one end to an input terminal and at the other end to dual position manual switch that is connected in parallel to a diode. This configuration allows the lighting element to be illuminated from either the control switches or via the manual switch, depending on the polarity.

Abstract: A method for controlling an airbag system is provided. The airbag system includes an airbag module which may be deployed at different rates to optimize performance of the airbag module to a given impact. The airbag system includes a control module, an impact sensor, a seatbelt restraint sensor and an airbag module. The airbag module includes an inflator having two independent squibs, a first one of the squibs being coupled to a first charge and a second one of the squibs being coupled to a second charge. The method monitors various vehicle dynamics and controls the generation of first and second squib pulses which cause the deployment of the first and second charges so as to optimize the rate at which the airbag is deployed for an impact of a given magnitude. The method also monitors the integrity of each squib circuit and when a fault in a squib circuit is detected, the deployment algorithm is modified to ensure that the airbag will deploy.