Night vision imaging systems produce visible images of an environment having minimal ambient light, which would otherwise not be visible to the human eye. Such systems are used by military and law enforcement units, as well as various civilian applications. One such application is improving the visibility of a vehicle driver during night, rain, fog, or other poor visibility driving conditions. The generated image of the area surrounding the vehicle may be processed to provide various driver assistance and safety features, such as: forward collision warning (FCW), lane departure warning (LDW), traffic sign recognition (TSR), and the detection of pedestrians, obstacles, oncoming vehicles, or other objects of interest along the driving route. The image may also be displayed to the driver, for example projected on a head-up display (HUD) on the vehicle windshield. A vehicle night vision system may also be used to enable autonomous driving at low light levels or poor visibility conditions.
An imaging system may operate using “active imaging” or “passive imaging”. An active imaging system involves actively illuminating the environment and accumulating reflections of the illumination light, whereas a passive imaging system merely collects existing ambient light or emitted/reflected radiation without additional illumination. For example, a passive imaging system may utilize a thermal or infrared camera, which senses differences in infrared radiation emitted by objects in the surrounding area and generates an “emission-based image” according to the sensed radiation differences. A passive imaging system may also collect light emitted or reflected from sources present in the environment, such as: vehicle high beams, streetlights, traffic lights, and the like. An active imaging system requires a light source to illuminate the environment and an imaging sensor to accumulate the reflected light, producing a “reflection-based image”. Active imaging allows for a visible image to be generated even when there is little or no ambient light present in the environment. The light source may be, for example, an LED, a filtered light bulb, or a laser diode, and may transmit light in the form of continuous wave (CW) or in a series of pulses. The image sensor may be semiconductor based, such as charge-coupled devices (CCD), or active-pixel sensors (APS) produced using the complementary metal-oxide-semiconductor (CMOS) or the N-type metal-oxide-semiconductor (NMOS) processes.
The technique of synchronizing the illumination pulses with the camera activation in active imaging systems in order to image a particular depth of field (DOF) is known as “gated imaging”. After the illumination pulse is transmitted, the camera remains in an off state (i.e., does not accumulate any reflected photons), while the pulse reaches the target area and light is reflected back toward the camera. When the reflected light is due to arrive at the camera, the camera is activated to open (i.e., to accumulate reflected photons). After the pulse is received, the camera is turned back off, while awaiting the transmission and reflection of the subsequent illumination pulse. The camera remains off for the duration of time required for the pulse to travel toward the target area and be reflected back, and is subsequently activated only for the duration required to receive the reflected light from the desired DOF. In this manner, the camera receives only reflections from the desired range, and avoids reflections from unwanted objects, such as particles in the atmosphere which may cause backscattering and reduce the contrast of the target area in the generated image. Gated imaging may also be employed to reduce the potential for oversaturation and blooming effects in the sensor, by collecting fewer pulses from shorter distances, thereby lowering the overall exposure level of the camera to near-field scenery and avoiding high intensity reflections from very close objects. Similarly, the light intensity or the shape of the illumination pulse may be controlled as a function of the distance to the target object, ensuring that the intensity of the received reflected pulse is at a level that would not lead to overexposure of the image sensor.
Vehicle-mounted imaging systems that operate solely using a reflection-based image (active illumination imaging) may sometimes produce unclear and indecipherable image content, such as insufficient contrast between potential objects of interest and the background, or insufficiently lit objects (due to the reflected signal intensity being too low). As a result, it may be difficult to ascertain with a high degree of confidence the presence of relevant objects in the environment (such as a pedestrian or a vehicle along the road), and to accurately identify whether they pose a potential hazard. A reflection-based image typically has a high resolution (e.g., at least VGA), where each pixel output is at least 8 to 10 bits if not more. Accordingly, a considerable amount of data must be processed in a reflection-based image in order to allow for object detection. The increased time and processing required to accurately determine potential hazards and relevant objects in the vehicle path based on such reflection-based images also necessitates a longer decision making period for the vehicle operator, which may increase the likelihood of a traffic accident. Finally, a single camera (or sensor) may be restricted to a particular spectral range, which may limit the object detection capabilities.
Conversely, vehicle-mounted imaging systems that operate solely using passive emission-based imaging provide very limited information, and are only capable of detecting objects in the environment that radiate above a sufficient level (or that are above at least a certain temperature) and that radiate in the selected wavelength range (e.g., infrared). Accordingly, such passive emission-based imaging systems typically fail to provide a comprehensive image of the entire environment, and can only provide the vehicle operator with limited information relating to relevant objects and potential hazards in the vicinity of the vehicle. Moreover, it is often difficult for an average person to properly understand and interpret a displayed emission-based image (such as a thermal image). Even for individuals that have experience and familiarity with these types of images, it usually still takes some time to process and register the connection between the contents of the thermal image and the real-world environment that is represented. Thus, the increased processing time to identify potential hazards in the thermal image also increases the decision making time of the vehicle operator, which ultimately raises the likelihood of a vehicle accident.
U.S. Pat. No. 7,786,898 to Stein et al., entitled: “Fusion of far infrared and visible images in enhanced obstacle detection in automotive applications”, describes a vehicle warning system and method that determines a danger of collision between the vehicle and an object in the vehicle environment. The system includes a visible (VIS) light camera, a far infrared (FIR) camera, and a processor. The VIS camera is mounted in the vehicle cabin and acquires, consecutively and in real-time, multiple VIS image frames of a first field of view (e.g., in the direction of travel of the vehicle). The FIR camera is mounted in front of the vehicle engine and acquires, consecutively and in real-time, multiple FIR image frames of a second field of view (e.g., in the direction of travel of the vehicle). The processor detects an object in at least one of the VIS image frames, and locates the detected object in at least one of the FIR image frames. The processor determines a distance between the vehicle and the object responsive to the location of the detected object in both the VIS and FIR image frames, and determines if there is a danger of collision between the vehicle and the object at least partially responsive to the determined distance.
U.S. Patent Application No. 2006/0006331 to Adameitz et al., entitled: “Method for representing a front field of vision from a motor vehicle”, describes a device and method that generates a representation of the field of vision in front of a vehicle, based on three detectors: a near-infrared (NIR) camera system, a far-infrared (FIR) camera system, and a sensor system (e.g., radar sensors and/or ultrasonic sensors and/or ultraviolet sensors). The information generated by each detector undergoes optimization, such as noise filtering, edge filtering, and contrast improvement, and is forwarded to a display after determining whether to superimpose the NIR data with the FIR data. If superimposition is carried out, the image areas of the two cameras are adapted to one another, and if appropriate also restricted. The optimized data of each detector also undergoes feature extraction to assist object detection. If an object which presents danger is recognized, a visual or audible warning is issued.
U.S. Pat. No. 8,525,728 to Lundmark et al., entitled: “Method of detecting object in the vicinity of a vehicle”, discloses a method and system for detecting objects in the vicinity of a driven vehicle. The vehicle is equipped with a forward-facing camera and side-facing cameras. A processor analyzes the camera signals to detect objects by employing one or more detection criteria. The detection is regulated by detection parameters that define the sensitivity with which objects appearing in the camera images are detected. The detected objects are classified into different categories, following which an indication may be provided to the driver and one or more vehicle safety systems may be activated as necessary. A counter maintains a count of the number of objects detected in an image, and passes the information to a parameter adjuster. The parameter adjuster adjusts the detection parameters in accordance with the number of objects detected in previous frames relative to an optimum number of detections, such that the processing capability of the processor is utilized as completely as possible, in order to maximize the possibility of detecting the most relevant objects and enhance vehicle safety.
USPTO Backgrounds
USPTO Backgrounds