Dashcam Designs for Clear Footage in Low-Light Conditions

Protective lens covers for vehicle cameras that illuminate the camera's view to improve image quality in low-light conditions and to prevent obscuring by rain, snow, dirt, mud etc. The cover has a lens, light source, and electrical connector to attach to the camera housing. The lens is a meniscus shape to focus the image. The light source provides illumination.

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An image-capturing device that can simultaneously capture color and infrared images with optimal exposure in both ranges. The device has an image sensor with an array of optical filters and photosensitive pixels. The filters transmit infrared light and visible light. The pixels respond to the filtered light. The device uses a computer to analyze brightness levels in the infrared and visible images. It then adjusts exposure parameters for the filters and pixels based on the analyzed brightness to capture optimized infrared and color images simultaneously. This allows balanced exposure in both ranges without sacrificing one over the other.

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A camera for vehicle safety and driver assistance systems that can reduce stray light entering the camera housing. The camera has a removable light-trap attachment that blocks light from reaching the lens. The attachment connects to the camera housing via engaging holding parts. The holding parts can be resilient hooks and fixed indents that snap together when the light-trap is attached, securing it to the housing.

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A vehicle camera that mitigates sudden brightness changes in images captured by the camera as the vehicle moves between sunny and shaded areas. The camera determines if there is a brightness boundary ahead where the light level changes rapidly. If so, it uses a strategy to gradually adjust exposure and brightness in the image processing to avoid sudden darkening or brightening when crossing the boundary. This prevents images from being over or under exposed when transitioning from sun to shade or vice versa.

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Image acquisition system that uses an image sensor with both visible light and infrared sensors to capture better images in low light conditions. The system determines the exposure time for the visible light sensor based on the ambient light level. This improves the quality of the visible light image. It also captures an infrared image using the infrared sensor. The infrared image is processed to generate a wide dynamic range (WDR) image. The visible light image and the WDR image are then fused to create a higher quality final image compared to just using the visible light image alone in low light conditions.

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A vehicle vision system that enhances night vision for a vehicle driver. The system uses two cameras facing forward - one with a wide field of view for machine vision applications, and one with a narrower field of view optimized for low light color capture. The narrow FOV camera has optics and spectral filters to provide enhanced color imaging even in low lighting conditions like night driving. The narrow FOV camera captures color video which is displayed to the driver for enhanced night vision, while the wide FOV camera is used for machine vision functions like object detection.

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Imaging device with improved low-light performance by combining visible and infrared images. The device has a visible light imaging element and an infrared light imaging element with different exposure rates. It combines the visible light image with the fast-rate infrared image and the slow-rate infrared image. This increases dynamic range without reducing frame rate compared to just increasing infrared exposure. The device also optimizes exposure for each element to prevent charge accumulation during high infrared light levels.

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Coordinated auto-exposure for vehicles with multiple cameras to improve object detection and safety in complex lighting conditions. The technique involves determining an optimal exposure time for multiple cameras with overlapping fields of view based on the lighting conditions in their shared view area. This allows consistent exposure for objects in the shared view despite differing lighting in their individual fields. The cameras are then synchronized to take pictures at the optimal exposure. This reduces discrepancies in object appearance across images for improved object detection and 3D modeling.

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Vehicular image capture system and method that improves image quality and object recognition from moving vehicles. The system captures a driving scene, extracts an object image, calculates the brightness distribution along a straight line through the object, and fine-tunes shutter speed, gain, or fill light intensity based on the brightness waveform. This adaptive exposure adjustment compensates for moving object motion blur and provides optimal exposure for the object while avoiding overexposure of the background.

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An in-vehicle camera system that can adapt to sudden changes in lighting conditions ahead of the vehicle. The system has a far camera and a near camera. When the far camera detects abnormal lighting due to an illumination change, it triggers aperture control on the near camera. But it delays starting the near camera aperture control until the vehicle reaches a specific timing based on distance or time. This prevents premature aperture changes. The system also cancels near camera aperture control if the far camera lighting normalizes during travel.

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Enhancing image quality from a vehicle's camera to enable autonomous driving in challenging lighting conditions. The method involves proactively and reactively adjusting a light-control feature on the vehicle to mitigate issues like blooming, glare, and lens flare when external light sources like the sun are present. If the image quality is expected to be low due to light conditions, the feature is adjusted to reduce the amount of light encountered by the camera. If a specific light source like a traffic signal is detected, the feature is adjusted to block that light. This improves image quality and allows accurate object detection for autonomous driving even in difficult lighting scenarios.

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Optimizing camera images in vehicles by selectively binning pixels based on light conditions. The technique involves determining light patterns around the vehicle using sensors, location data, etc. Then for each camera image, binning pixels together in dark regions to improve handling and viewing, but leaving pixels unbinned in bright regions for better resolution. This results in frames with binned and unbinned regions covering both light conditions.

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Image processing device for vehicle cameras that improves object recognition in low beam headlight conditions by adjusting pixel values. The device acquires images from the vehicle's camera, determines if the headlights are in low beam mode, and then adjusts the relationship between object luminance and pixel values to compensate for the low light conditions. This raises pixel values in areas of the image with low luminance objects to improve recognition.

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Camera system for vehicles that adaptively applies image correction based on scene brightness to compensate for lens vignetting without reducing frame rate. The camera activates a lens correction function to compensate for light falloff in the image edges caused by wide-angle lenses. But it only does so when the scene brightness is low. This prevents false brightness interpretation due to dark current, which would normally reduce frame rate. The camera captures scene brightness and uses it to determine when to enable lens correction. This allows compensating for lens vignetting without sacrificing frame rate in low light conditions.

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Adaptive histogram spreading for cameras in vehicles to improve image quality in low light conditions while preventing over-darkening of images. The method involves setting limits on the output pixel values based on the environment brightness. This prevents further darkening of already dark pixels when histogram spreading is applied in low light. The limits are determined by acquiring a parameter related to the environment brightness, like the sensor value from a dedicated brightness sensor. By dynamically limiting the output pixel values based on the environment brightness, the camera avoids over-darkening in low light while still providing improved contrast compared to the raw image.

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Reducing motion blur in low light conditions by optimizing exposure time based on image brightness levels and distribution. The camera changes exposure time based on the brightness level and brightness distribution in an image. It uses two sensors, one to capture a baseline image with standard exposure, and another to capture multiple images with varying exposures. By analyzing the brightness levels and distribution in the baseline image, the camera determines the optimal exposure time for the second sensor. This allows capturing a blur-reduced image in low light without overexposing or underexposing the entire scene.

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Vehicle driving environment recognition system that improves nighttime visibility and precision by dynamically adjusting the camera exposure and headlight brightness based on detected vehicles ahead. The system uses an onboard camera to capture the environment in front of the vehicle. It recognizes nearby vehicles and sets the headlight distribution and camera exposure accordingly. When no vehicles are detected, it uses a mode with multiple exposure levels to capture detailed scenes. But when vehicles are detected, it switches to a fixed exposure to prevent blooming from bright lights. This improves nighttime visibility and recognition accuracy by optimizing camera and headlight settings based on the environment.

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Brightness adjustment system for surround view cameras in vehicles that reduces differences in brightness between images from multiple cameras to improve consolidated views. The system captures images from multiple cameras with adjustable exposure times. It determines brightness parameters from the images and adjusts exposure times to match parameters between cameras. This balances brightness across the consolidated view.

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