Patent Description:
<CIT> discloses an image processing apparatus and method, wherein presence or absence of flicker in image data is detected based on information received from a flicker detection section. If flicker is detected, a processor section determines the light source frequency of a subject light source that causes the flicker. The exposure time of an image capturing element is set to a value matching the light source frequency, whereby the occurrence of flicker is suppressed.

<CIT> discloses a method and a device for recognising a pulsing light source, in which a sequence of individual images is acquired with a light sensitive sensor. In an evaluation unit, all or at least some of the picture points of each individual image are examined with regard to at least one predefined feature.

According to the invention, a display system, a rear-view assembly and a method of processing streamed images are provided, respectively, in claims <NUM>, <NUM> and <NUM>.

These and other features, advantages, and objects of the present invention will be further understood and appreciated by those skilled in the art by reference to the following specification, claims, and appended drawings.

Reference will now be made in detail to the present preferred embodiments of the invention, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numerals will be used throughout the drawings to refer to the same or like parts. In the drawings, the depicted structural elements are not to scale and certain components are enlarged relative to the other components for purposes of emphasis and understanding.

A common problem in rendering streaming video data captured from an imager occurs when the object being imaged is an amplitude modulated (AM) light source. A very common example of this type of light source is one which is pulsing on/off at some periodic rate, like a vehicle lamp assembly constructed with light emitting diodes (LEDs), where the LEDs are pulse-width-modulated (PWM), which is a subset of possible amplitude modulation methods. The PWM period and duty cycle result in the LEDs being turned on and off at some periodic rate, and a camera taking streaming images of this lamp assembly will capture successive images where an LED may be 'on' in one or more consecutive images, and then 'off' in one or more subsequent images. Other examples of AM light sources include the flashers on an emergency vehicle (which may also be comprised of PWM LEDs), a turn signal on a vehicle, or a fluorescent light source in a tunnel or parking garage.

For many of the exemplary AM light sources listed above, a human observer of the light source does not perceive any flicker in the 'on/off' pattern since the frequency of the on/off pattern is higher than the human vision system can perceive (PWM LED headlamp/tail lamp assemblies being a prime example). But in imaging the AM light element with an electronic camera system, the exposure time, frame rate, and shutter scheme (rolling or global) used when capturing the light element at a particular pixel in the imager array may result in some images showing this pixel to be imaging an 'on' state of the light element, and successive images showing this pixel capturing the 'off' state of the light element. In attempting to render these images to a display, at some display frame rate, the display system may end up presenting the human observer an 'on/off' pattern that is discernible as a 'flickering' light.

<FIG> shows an image system <NUM> according to a first embodiment. As shown, image system <NUM> includes a camera <NUM> that captures images of a scene and outputs streamed video images of the scene, and a display system <NUM>, which includes an image processing unit <NUM> that receives the streamed video images and processes the images (as discussed in detail below) and outputs the processed streamed video images, and a display <NUM> that displays the processed streamed video images.

The methods and processing sequences described herein are intended to mitigate the 'flickering' phenomena seen in rendered AM headlamps and tail lamps (especially targeted to PWM LED assemblies, but not limited to lighting of that technology). As described below, the platform on which these methods may be implemented is part of an automotive mirror replacement system, where a vehicle mirror is replaced by camera (lens plus digital imager) <NUM>, image processing unit (serial processor and/or ASIC/FPGA) <NUM>, and electronic display (LCD/LED panel) <NUM>. The methods described herein may be incorporated in the image processing unit <NUM> in the above system <NUM>. As shown in <FIG>, the method steps may be performed in the following sequence (as would occur on the image processing unit <NUM>): <NUM>) receiving the streamed video images (step <NUM>); <NUM>) detection of the PWM LED (or AM) lights in a succession of the streamed video images (step <NUM>); <NUM>) differentiation/classification of the PWM LED (or AM) elements (which are part of a headlamp or tail lamp assembly) from other illuminating objects in the scene which have time-varying brightness levels (e.g. emergency vehicle lights) (step <NUM>); <NUM>) tracking of the pulsed lights over time (step <NUM>); <NUM>) correction of the flicker artifact associated with these rendered lights in a way that is appropriate to the specific type of light source (step <NUM>); and <NUM>) supplying the processed video streamed images to display <NUM> (step <NUM>). Possible techniques for each of these steps are detailed below.

Multiple methods exist for performing step <NUM> involving detection of time-varying lights in a sequence of captured images. In the problem area of a rearview mirror replacement system (based on an electronic camera <NUM>, an image processing unit <NUM>, and a display system <NUM>), PWM LED lights that may need to be detected are those originating from vehicle headlamp and tail lamp systems. These lights are related to vehicles, which are on the same roadway as the vehicle outfitted with the mirror replacement system. The search space for the PWM LED lights of interest thus can be influenced by roadway detection, where an auto-aim or lane detection system can narrow the light search space to the vertical region above the detected road boundaries (from a lane detection system), or around the focus of expansion (from an auto aim system), and discriminated from stationary non-vehicle light sources. In this reduced search space, methods exist in existing high beam control systems to detect PWM LED lights as disclosed in commonly-owned <CIT>, <CIT>, <CIT>,<CIT>, <CIT>, <CIT>,<CIT>,<CIT>,<CIT>, <CIT>,<CIT>, <CIT>,<CIT>, <CIT>,<CIT>,<CIT>,<CIT>,<CIT>,<CIT>, and <CIT>.

Additionally, detection methods such as frame subtraction may be used for detecting time-varying light sources, where successive images are subtracted from one another to produce temporal difference maps. The resultant maps are then processed by routines (implemented in software or in ASIC/FPGA fabric), which perform some combination of thresholding and/or filtering to identify spatial areas in the map where there were significant changes in pixel brightness between the two source images. The absolute value of the difference data indicates the magnitude of the change in pixel intensity between frames, and the sign of the difference data indicates whether the change in a pixel value between frames is associated with a light source brightening or darkening. The frame data used to generate these temporal difference maps may be raw data from a Bayer patterned image, luminance data extracted from the image, or some other image form extracted from the image processing path. On a typical roadway scene, the most significant deltas in pixel values between a pair of frames (referenced to a single pixel location), tend to be related to these PWM LED (AM) lights which are going from extremely bright, to fully off. Motion artifacts can also contribute to temporal changes in image values at the pixel locations, but in the search space of the roadway imaged by the vehicle, this motion is quite small -- as the image capture rate is rapid compared to vehicle dynamics, and the brightness changes related to objects which do not produce their own illumination is also quite reduced (imaging a vehicle body at a pixel in the first frame to a part of the vehicle bumper in the next frame does not produce as significant a luminance change than the PWM LED is exhibiting in its on/off sequencing).

Other methods of detecting the presence of AM lights may be leveraged from the imager implementation, where some imagers may supply information (to the pixel level) on whether the scene brightness changed state during the pixel exposure time (especially for an imager such as an HDR CMOS imager).

As described below, the methods for correctly rendering pulsed lights tend to fall in the category of adding image content to 'brighten' the pulsed light location for durations when the light is captured as 'off' and addressing incorrect color measurements induced by the time-varying nature of the lights. The classification operation (step <NUM>) is applied to discriminate between the types of time-varying light sources that introduce the brightness and /or color errors. To ensure only the desired pulsed lights are corrected (and not, for example, motion artifacts), light source classification maybe performed to influence the correction step <NUM>. Methods of classifying PWM LED lights are known in high beam control systems such as those disclosed in commonly-owned <CIT>,<CIT>, <CIT>, <CIT>, <CIT>, <CIT>,<CIT>, <CIT>,<CIT>, <CIT>, <CIT>, <CIT>,<CIT>,<CIT>, <CIT>, <CIT>,<CIT>, <CIT>,<CIT>, and <CIT>. But other options exist in the use of temporal changes, color, brightness and location. The options for use of brightness and color for classification are greatly enhanced by the use of a Bayer patterned, High Dynamic Range (HDR) imager in the camera system, since bright objects are not saturated with an HDR imager, and the Bayer pattern contributions can be demosaiced to determine color of very bright lights. Object detection systems that classify vehicles can also be used to influence the classification of PWM LED headlamps/tail lamps, by limiting search windows to areas associated with the identified vehicles.

Basically, the classification can be used to distinguish between those flickering lights that are humanly perceivable when viewing the lights directly from those lights that are not humanly perceivable as flickering when viewing the lights directly. This way, the images of the light sources may be selectively modified based upon such classification so that the light sources will appear in the displayed scenes as they would otherwise appear to a human viewing the lights directly.

The step of temporal tracking of pulsed lights (step <NUM>) can be performed using the techniques for tracking vehicle lights as described in known high beam control systems such as those disclosed in commonly-owned <CIT>, <CIT>, <CIT>, <CIT>, <CIT>, <CIT>,<CIT>,<CIT>,<CIT>, <CIT>,<CIT>, <CIT>, <CIT>, <CIT>,<CIT>, <CIT>, <CIT>, <CIT>,<CIT>, <CIT>, and<CIT>. This temporal and spatial tracking is useful when selectively modifying the images in order to brighten pixels corresponding to the expected location of the flickering light source in those modified images.

Step <NUM> involves resolving light flicker for rendering on display <NUM>. With the AM (or pulsed) lights which need to be addressed for display flicker reduction identified, the method of flicker reduction can be performed by substituting low pixel values (from 'off' situations), with values which correspond to levels associated with 'on' situations. The pixel value replacements can be performed at the raw level (a Bayer pattern color associated with the replaced pixel), or at a later processing step in the processing subsystem. There are advantages to performing pixel replacement at the post-demosaic step, and color can be preserved for the PWM light by creating the correct balance of red, green and blue contributions. To maintain the displayed boundaries of AM light objects when pixel substitution is being performed, some image processing steps may be used to predict the object outline in an upcoming frame by using the tracking information of step <NUM>, and an object shape detection routine.

Alternatively, the temporal difference maps from the detection step can be used to define the region of pixels to be substituted (since they represent the pixels which have changed state between frames), with better results possible from using maps that incorporate more than just a two frame difference. One possible implementation of this method would involve creating difference maps of pixel values (by location) across sequences of frames, replacing pixel values that have been determined to be producing images of pulsed PWM LED lights with an average of the highest M values in an N frame sequence (M less than N), if the average of highest M values exceeds some threshold. If analysis of overall image luminance and object color is used, this replacement method may also be used to replace PWM LED detection, classification, tracking and replacement.

A forward-facing turn signal is one example of a time-varying light source that could be detected, classified, and corrected using the ideas disclosed here. Unlike a PWM light, whose row-to-row values on the imager may vary greatly due to beat frequencies, a turn signal's frequency is significantly lower than a camera's frame rate (<NUM>-<NUM> as opposed to <NUM>-<NUM>). This results in areas of the light turning on and off at the turn signal's frequency. This spatial consistency within the boundaries of the light, coupled with a detected frequency that is indicative of a turn signal and a yellowish hue, could allow classification of a light as a turn signal as it is tracked. Once the system knows what kind of light it is, the system can fix it by increasing its yellow saturation, creating more visual appeal, but leave its on/off behavior alone.

A PWM LED tail lamp is a difficult object to image and visualize correctly because it is typically not relatively bright compared to the background. In addition, for rolling shutter cameras, each row of pixels may have a sharply different level of brightness, and this can be exacerbated by the spatial effects of the Bayer filter, leading to many artifacts in both chrominance and luminance. However, some of these characteristics-row-to-row variation, local colors that are wildly different, and colors and intensities that change drastically from frame to frame, etc.-in addition to other characteristics-location in the image, predominance of brighter red pixels, motion toward the focus of expansion, frequency estimation on the light modulation, etc.-could allow classification of these lights with high accuracy. Fixing PWM LED tail lamps could be performed by making the colors a uniformly saturated red while choosing a luminance from the detected range, which would end up being visually appealing and remove harsh artifacts.

Referring now to <FIG>, a schematic diagram of a vehicular implementation of the above embodiment is shown. A vehicle <NUM> is shown that is driven by operator <NUM>. One or more cameras <NUM> are operative to view a scene <NUM>. In the example shown, scene <NUM> is generally behind vehicle <NUM>. However, camera <NUM> may be oriented in a variety of ways to view scenes at other locations about vehicle <NUM> including, but not limited to, the sides, back, front, bottom, top, and inside. In the example shown, signals representative of the scene are sent via channel <NUM> to an image processing unit <NUM>. Image processing unit <NUM> produces an enhanced image of scene <NUM> on one or more displays <NUM>. Input from an optional ambient light sensor <NUM> and one or more direct glare sensors <NUM> is also available to image processing unit <NUM>.

In a particularly useful embodiment, a rearview assembly <NUM> (<FIG>) is augmented or replaced by imaging system <NUM> having cameras <NUM> which cover a wide field of view to the back and sides so that pedestrians or other objects directly in back of vehicle <NUM> may be seen and so that oncoming traffic from the sides may be seen. The system is designed so that, when backing out of a parking spot, oncoming vehicles may be seen before backing into the lane of travel. This requires camera system <NUM> with a near <NUM>° field of view or several camera systems <NUM> mounted near the rear of the vehicle. An analogous system with a camera or cameras <NUM> mounted near the front of the vehicle <NUM> is adapted to view cross traffic at a "blind" intersection before entering the lane of travel of the cross traffic. These are desirable applications for the present invention which supplement the viewing function of conventional rearview mirrors.

<FIG> show an example of a rearview assembly <NUM> having a housing <NUM> with a display <NUM> and an optional mirror element <NUM> positioned in front of the display <NUM>. A user switch <NUM> may optionally be provided for tilting of the mirror element <NUM> and/or display <NUM> to reduce glare on the display <NUM> when activated. Examples of such a rearview assembly <NUM> are known and are disclosed in commonly-owned <CIT>, <CIT>, and <CIT>. The optional ambient light sensor <NUM> and a direct glare sensor <NUM> may be incorporated in rearview assembly <NUM> as is known in the art. Further, image processing unit <NUM> may be disposed in the rearview assembly <NUM>. Rearview assembly <NUM> may be an interior rearview assembly as shown in <FIG>, or may be an exterior rearview assembly.

Claim 1:
A display system (<NUM>) for a vehicle (<NUM>) equipped with a camera (<NUM>) for supplying streamed video images of a scene (<NUM>) rearward of the vehicle (<NUM>), the display system (<NUM>) comprising:
an image processing unit (<NUM>) for receiving the streamed video images and processing the streamed video images; and
a display (<NUM>) for displaying the processed streamed video images,
wherein to perform processing of the streamed video images, the image processing unit (<NUM>) is configured to:
detect amplitude-modulated light sources in the streamed video images,
classify the detected amplitude-modulated light sources into one of several possible classifications,
wherein the image processing unit (<NUM>) classifies the detected amplitude-modulated light sources into at least two classes where a first class of detected amplitude-modulated light sources having a flicker not perceivable by a human when viewed directly by the human, and a second class of detected amplitude-modulated light sources having a flicker that is perceivable by a human when viewed directly by the human,
select the streamed video images in which an amplitude-modulated light source is detected that flickers based upon the classification of the amplitude-modulated light source, and
modify the selected streamed video images to correct for flicker of any amplitude-modulated light sources in the selected streamed video images,
wherein modifying (<NUM>) the streamed video images in which an amplitude-modulated light source is detected that is classified in the first class comprises substituting pixels representing each of the detected amplitude-modulated light sources that is classified in the first class such that the pixels representing the detected amplitude-modulated light source are always at a state so that when the processed streamed video images are displayed, each of the detected amplitude-modulated light sources that is classified in the first class appears to have no perceivable flicker, and
wherein the light sources classified in the second class are not corrected for flicker.