WO2011000392A1 - Procédé et système de caméra permettant d'améliorer le contraste d'une image de caméra - Google Patents

Procédé et système de caméra permettant d'améliorer le contraste d'une image de caméra Download PDF

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Publication number
WO2011000392A1
WO2011000392A1 PCT/EP2009/004783 EP2009004783W WO2011000392A1 WO 2011000392 A1 WO2011000392 A1 WO 2011000392A1 EP 2009004783 W EP2009004783 W EP 2009004783W WO 2011000392 A1 WO2011000392 A1 WO 2011000392A1
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WO
WIPO (PCT)
Prior art keywords
image
camera
brightness
correction function
contrast
Prior art date
Application number
PCT/EP2009/004783
Other languages
English (en)
Inventor
Christopher Gideon Reade
Patrick Eoghan Denny
Original Assignee
Hi-Key Limited
Application Solutions (Electronics And Vision) Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hi-Key Limited, Application Solutions (Electronics And Vision) Ltd filed Critical Hi-Key Limited
Priority to PCT/EP2009/004783 priority Critical patent/WO2011000392A1/fr
Publication of WO2011000392A1 publication Critical patent/WO2011000392A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/14—Picture signal circuitry for video frequency region
    • H04N5/20—Circuitry for controlling amplitude response
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/80—Camera processing pipelines; Components thereof
    • H04N23/82—Camera processing pipelines; Components thereof for controlling camera response irrespective of the scene brightness, e.g. gamma correction
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/44—Receiver circuitry for the reception of television signals according to analogue transmission standards
    • H04N5/57—Control of contrast or brightness

Definitions

  • the invention relates to a method and a camera system for improving the contrast of a camera image, such as preferably used in driver assistance systems for motor vehicles, according to the preambles of Claim 1 and 18.
  • Camera images or video images are used in image- or non- image evaluating driver assistance systems, or else what are referred to as vision-based driver assistance systems, for sensing the surroundings, and in the known syscems objects, obstacles, rc ⁇ dv.'ay boundaries and lane boundaries as well as distances thereto are determined on the basis of the camera images.
  • image sensor which are referred to as imagers are used in what are referred to as vision- based surroundings-sensing systems and they then supply a camera image of the sensed surroundings, which is also referred to as a sensor image and whose pixels or image areas can be evaluated in terms of intensity, contrast, colour or other parameters using
  • EPl 475 745 Al discloses such an evaluation of pixels of a video image, in which evaluation of a frequency distribution of the brightness values over the surface of the image sensor is performed. Areas are defined in which the pixels are evaluated in order to improve the contrast and the brightness values of the pixels are changed by means of a correction data calculation by comparing the brightness values with pixels which are associated with surrounding areas . If a camera in, for example, a vehicle captures a scene on a roadway, the brightness content of the scene should be as far as possible in a range which covers a numerically appropriate range for evaluation in the computer system. If a scene has high dynamic range here, i.e.
  • the mean value of the numeric output data of the video image corresponds approximately to the mean range of the brightness of the scene.
  • the dynamic range of the possible output data is greater in terms of the brightness than the representation capability of the camera. In this context, it is then necessary to decide how the captured video information is to be displayed in an optimum way.
  • the camera usually changes the exposure values and/or the amplification values, but this entails the effect that if it reduces the amplification and/or the exposure to an excessive degree, the relatively bright areas of the image have content and structure but the relatively dark areas of the image are then virtually impossible to evaluate. If the amplification and/or the exposure are increased, the relatively dark areas of the image exhibit content and structure but the
  • the camera itself decides on the general exposure in the sense that it automatically adjusts the exposure of the camera to give a sensible picture. If the camera evaluates that a scene looks particularly bright it reduces the exposure time and if it looks particularly dark it increases the exposure time. There is a specific pair of routines that do this in the camera, one of which is typically called the Automatic Exposure Control (AEC) and Automatic Gain
  • AGC AGC Control
  • the first of these increases the signal value from a pixel by letting in light for a longer period.
  • the second of these controls amplification of the signal from a pixel by increasing the gain on an amplifier coming from a pixel.
  • the exposure of the camera is probably well chosen to give a good picture and there is enough light so the voltages recorded in the pixels don't need to be artificially amplified by changing the amplifier gain. So the exposure time is reasonable and the gain is low. If the light level drops, it is common to increase the exposure time to let in more light. This is an
  • Step f) go back to step a) Steps d) and e) above subject to a hysteresis to prevent the overall image changing too fast when some features in the scene become brighter or darker, otherwise it would be possible in a driver assistance system to start the driver or may cause him too much variation in the input image, which might confuse the other algorithms on the image sensor.
  • the exposure time increases until it reaches a limit.
  • This limit is usually related to the frame rate, since it is not possible to expose an image longer than a frame,- if it's done it is not possible to output a frame within the frame period.
  • the exposure reaches the limit there isn't really any dynamic AEC and the AGC starts to work, increasing the gain.
  • the gain is at a maximum and the picture is dark and noisy.
  • the AGC gain drops to a minimum
  • the AEC drops the exposure to a minimum and eventually a completely white image is obtained.
  • the invention is based on a method for improving the contrast of a camera image comprising the steps of evaluating the brightness distribution of the image and applying a contrast correction function to the image, whereas evaluating the brightness distribution includes determination of a spatial brightness distribution of the image, and whereas the contrast correction function is varied depending on the spatial brightness
  • the advantage archived with this method is that the spatial brightness distribution can be used to detect certain, a prior known lighting condition, in which an automatic gain or exposure control of the camera would lead to unsatisfying results. If such lighting
  • correction function is automatically varied accordingly in order to improve the contrast distribution of the image.
  • the image comprises a great upper area containing the bright sky and lower area containing the significantly darker foreground.
  • These lighting conditions will be referred to as Bright Sky Darkening Foreground (BSDF) .
  • BSDF Bright Sky Darkening Foreground
  • the camera could therefore reduce the enhancement and/or the exposure to such an degree that the foreground would be dark and low in contrast for optimum image evaluation.
  • the method according to the invention is designed to detect such situations by evaluating the spatial distribution of the brightness in the image and to vary the correction function accordingly in order to improve the contrast distribution.
  • the contrast distribution is preferably corrected such that the contrast is
  • the method according to the invention advantageously makes use of priori knowledge for both detection of certain difficult lighting conditions and decision on how the contrast
  • Such a priory known, difficult lighting conditions could also occur in connection with vehicle mounted cameras for driving assistance systems, if, for example the image taken by the camera contains an bright area due to reflections at the vehicles body.
  • these reflections can be reflections of light from a vehicle light at a vehicle body part.
  • Other examples of such lighting conditions include reflections of light at a wet road surface.
  • the different areas can, however, also be defined by a relatively dark, inner area which is more important for the evaluation, in particular by entrances to tunnels or garages, and by a surrounding, relatively bright area. It is also possible for the different areas to be defined by a relatively bright area owing to
  • reflections or salient colouring and a relatively dark area which is more important for the evaluation.
  • the areas which are relatively bright due to reflections or salient colouring can be parts of the vehicle carrying the cameras.
  • the method for evaluating the image data is carried out with essentially two method blocks.
  • heuristic detection and, on the other hand, correction of the image data is performed.
  • the data stream which contains the image data, i.e. the brightness or the chroma values, at the output of the carriers, is subsequently checked in the image-evaluation means to determine whether the
  • This may involve preferably heuristic methods in which sufficient definitive information about the structure of the image can be acquired by evaluating less image data, i.e. in order to see whether areas of the data stream
  • the upper area of the image is usually bright and relatively homogenous in this context, and the lower part is dark and also relatively homogenous. It is therefore possible for a distribution of the image data to be processed to be performed as a function of the brightness of the area in accordance with the
  • the detected spatial brightness distribution is compared to an predetermined brightness distribution in order to determine, if BSDF or equivalent predetermined lighting conditions are present.
  • distribution preferably includes determination of the brightness at predetermined image locations. In this way the a priory knowledge is used to reduce the necessary image processing amount.
  • the ⁇ pdLidl bx iyhLness distribution of the image can be evaluated along at least one predetermined geometrical axis or curve.
  • the axis can be a vertical axis in order to detect a BSDF situation. For other lighting
  • the axis can horizontal in order to detect for example that the image contains a section with reflections. It should be noted that a straight axis could appear curved in the picture due to image
  • distribution can comprise localization of image areas of a predetermined minimum size, where the brightness is below and/or above a predetermined threshold.
  • the correction function is varied, when the image contains at least one boundary section, where the brightness exceeds a predetermined threshold.
  • This boundary section can be located at the upper vertical boundary of the image and contain a bright sky.
  • the method is designed to determine, if the image contains at least one bright image section, where the brightness exceeds a predetermined threshold, and at least one dark image section, where the brightness is below a predetermined threshold.
  • distribution comprises the step of dividing the image into lines and/or fields in order to simplify image processing.
  • the fields and/or lines can then be
  • the correction function preferably improves the
  • the image correction function is a gamma correction function, whereas the slope of the gamma curve is varied depending on the spatial
  • a colour correction function can be applied to the image, whereas the colour correction function is varied depending on the spatial brightness and/or colour distribution .
  • the proposed method can preferably be applied in surroundings -recognition systems for driver assistance systems with cameras which are mounted on vehicles in moving or stationary traffic, in which case the
  • the invention can also be applied to static cameras or a scene that is or isn't changing.
  • the method according to the invention can be performed on a camera system comprising a digital camera, image evaluation means for evaluating the brightness
  • the image evaluation means are determined for evaluating the spatial brightness distribution of the image and that the correction means are determined for varying the contrast correction function depending on the spatial brightness distribution of the image.
  • the camera system preferably comprises a digital camera is video camera including a video data generating element that is determined to perform an automatic exposure and/or gain control at the pixel capture level, whereas the video camera is connected to a
  • DSP Digital Signal Processor
  • the correction method can preferably operate according to a gamma correction function which respectively selectively amplifies or attenuates the image data of the areas.
  • the image data can be amplified, in particular in relatively dark areas, in such a way that they produce a higher contrast than the contrast which would result from average brightness of the video image .
  • gamma correction function is applied to image data from a video data generating element (i. g. an imager) whose data were gathered using general automatic exposure and/or gain control mechanisms applied at the pixel capture level .
  • the camera delivers a picture which, statistically, will have a reasonably good amount information for a general scene.
  • the important advantage of the invention is that the imager exposure itself is not used to change the DSP gamma.
  • the exposure of the imager simply makes sure that a sensible value is provided to the camera.
  • a principle advantage of this BSDF algorithm is that it doesn't really care what the exposure of the camera is doing but is generally applicable. It is possible to experiment with manipulating the otherwise autonomous behaviour of the cameras for the purposes of some applications, but this is potentially a highly unstable approach.
  • leaving AEC/AGC to the sensor delivers a body of image data which has structure that may be difficult or impossible for a human viewer to perceive without post-processing, to the DSP and BSDF then makes this hidden structure perceivable to the user by dynamic post-processing of the output gamma of the DSP.
  • the camera system is particularly suitable for a motor vehicle especially as part of a camera based driving assistance systems that takes a video image of the vehicle surroundings and displays the image on screen for inspection by a driver.
  • the camera system can be connectable to a network, in particular a bus system of the vehicle, and comprise means to receive additional data from the network, if information on if a vehicle light is turned on.
  • the method according to the invention can be carried out by a computer program or product which comprises computer-readable program means which are stored on a computer-compatible medium and which, when the computer program product is run on a microprocessor with associated storage means or on a computer, cause said microprocessor or computer to carry out a method or an arrangement for carrying out a previously
  • Figure 1 is a schematic illustration of a vehicle on a carriageway with a camera as a component of a
  • Figure 2 shows video images from the camera before and after correction of brightness ranges
  • FIGS 3 to 6 show schematic images with image data analysed according to the invention.
  • Figure 7 shows a profile of a gamma correction function for correcting the contrast of the image.
  • Figure 1 is a schematic image of a diagram in which a camera 1 on a vehicle 2 captures images in a field of view 3.
  • Tile image C ⁇ ptur ⁇ ci oy uric camera ⁇ is image processed by Digital Image Processor and transmitted to a display insides the vehicle's 2 cabin for inspection by the driver.
  • the image to be captured or the scene has a structure which is referred to below with a BSDF structure, i.e. it has an upper bright, relatively homogenous area 3a and a lower dark, and also relatively homogenous area 3b.
  • a BSDF structure i.e. it has an upper bright, relatively homogenous area 3a and a lower dark, and also relatively homogenous area 3b.
  • an image-evaluation means 4 in the vehicle 2 the method which is described subsequently can be carried out with different numerical criteria for the areas 3a and 3b.
  • Figure 2 shows such an image 5a and 5b, each with different numerical criteria.
  • the left-hand image 5a shows the original image data
  • the right-hand image 5b shows the image data corrected according to the invention.
  • the image 5a is analysed here, for example, in a vertical raster, which has different brightness values here in the direction from the top to the bottom.
  • the resulting reliability of three methods is given in the scale 6 with the upper three numbers (100 in each case) .
  • the fourth number 100 below is the resulting overall reliability.
  • the lower number 50 represents the correction intensity, with a quadrant correction, which is known per se, being assumed here.
  • dots 7 and the histogram 8 are shown here only for the purpose of explanation and are not shown in the application, but rather only used in the image- evaluation process.
  • Figure 3 shows a representation of the structure of image 5a according to Figure 2 as an image 5c with coarsely screened areas which respectively represent different brightness values.
  • a first method shown in Figure 4, a number of m horizontal fields relating to the upper or lower transgression of a brightness threshold are sampled in a predetermined number of n vertical lines. From both figures it is apparent that in particular the area covering the lower approximately 2/3 of the video image is relatively dark and a correction is appropriate here.
  • the image is therefore divided into fields in a predefined raster and an average brightness per field is determined, so that each field can then be identified and marked as "bright” or “dark” . It is therefore possible to analyse separate patterns for bright and dark pixels with respectively positive results for fields which are to be corrected and negative results for fields which are not to be adapted.
  • Figure 5 shows an evaluation of fields which are formed, for example, according to the gradient method.
  • This method forms perpendicular gaps between fields and is capable of largely eliminating small changes which are caused by noise or the like, and it generates a cumulative difference.
  • a counter can be increased here for gaps which become cumulatively darker, and can be reduced for gaps which become brighter. If the counter reading exceeds a threshold, this method accepts the image for further processing.
  • Figure 5 shows dark pixels as a darkening gradient and bright pixels as a gradient which becomes brighter, and the series at the bottom of the image according to Figure 5 represents the final cumulative gradient.
  • Figure 6 also shows a method with detailed sensing of grey values in the fields of the image in order to permit a positive decision in respect of a correction.
  • This method operates along horizontal series of fields and detects the changes in predefined pixels between adjoining fields, and in this context the number of pixels per field should be at least 40.
  • results are therefore assigned for correction only if the brightness of at least one of the pixels is below a predefined dark limit.
  • the results which are produced can then be weighted in five horizontal bands, and if the uppermost band is the first, the greatest weighting can be in the third and fourth bands.
  • the described method can function very well if the image which is to be evaluated is a-priori capable of improvement but additional manipulation with a more geometric method is necessary in order to concentrate on a BSDF structure. It is therefore necessary to check continuously whether the potential of the image data is sufficient for a correction. For example, a background with trees could certainly be given a higher weighting but blunt flat objects without a distinctive structure could be ignored. Normally, in these cases an
  • black pixels can be correspondingly weighted as an extreme difference (+1)
  • moderately dark grey pixels (+2) and white high-resolution pixels (-1) can be correspondingly weighted.
  • the previously mentioned method is applied to the Y information of the image data and therefore to the brightness control, but it is also alternatively possible to apply it to the colour information of the image data (Cb and/or Cr chroma) , since there are several possible
  • the correction with which the image data at the output of the camera 1 are further processed is carried out in such a way that the criteria of the previously described BSDF structure are detected and then a gamma correction is applied to the effect that the image data are weighted by means of the gamma correction function in such a way that the information of the image data in the dark areas of the image can better evaluated and presented.
  • Figure 7 shows such a gamma correction function 10 which is known per se and which represents the change of the Y input signal in relation to the brightness represented in the video signal with respect to a Y output signal.
  • the arrow 11 is intended to indicate how the bend in the gamma correction function 10 is pushed upward as a function of the order of magnitude of the BSDF structure in order to improve the information content of the darker areas .
  • the gamma correction function 10 which is used here differs from the gamma correction function which is usually applied in phosphorescent screens, in particular in cathode ray tubes in television sets, in having greater flexibility. If, for example, adjacent pixels of the video image have brightness values which are very close to one another, those pixels do not provide much contrast; on the other hand, if these brightness values have a large difference, they provide a relatively large contrast. So that the video image is improved in the darker areas, the gradient of the gamma correction function 10 must be increased for relatively low Y input signal values . However, since the overall range of the Y input signal values and the overall range of the Y output signal values have a similar order of magnitude, increasing the gradient of the gamma curve in an area (the
  • the gamma of the gamma correction function 10 has therefore been changed in order to acquire a larger gradient in the relatively dark areas and a smaller gradient in the middle of the bright areas .
  • a contrast which is closer to the required visual definition and also provides contrast and structure in the relatively dark area means a greater positive effect than the associated negative effect of the reduced contrast in the relatively bright areas .
  • the colour and/or other light effects of the vehicle can influence the image data in such a way that they either become too bright Oi " too dark. If it is too dark, there are possible ways of improving the bright scene information such as a sunlit carriageway behind the visible edge of a shadow thrown by the
  • the method according to the invention may also be helpful if the side of a bright vehicle is bright in a camera which is facing sideways or if a dark vehicle is in relatively dark surroundings in daylight .
  • the colour of the vehicle can also already be
  • the method can also be used as a countermeasure to the oversaturation due to a strong light source in a relatively dark scene such as that from a vehicle lamp at dusk.
  • the concept according to the invention can also be applied to scene information which requires so-called white balance, for example in order to calculate the degree of white balance through knowledge of the colour of the vehicle so that the degree of white balance can be reduced.
  • a video system calculates the image data in such a way that the scene contains a similar proportion of the colours red, green and blue in order to reduce the effect of the colour of the lighting element on the illuminated objects, and therefore to ensure that the colours which are seen by the user represent the object more than the light source. This is a so-called "grey world assumption" and functions in an extremely acceptable way for most scenes.
  • the red proportion must be suppressed in the case of a relatively neutrally illuminated element in the field of vision or the blue and green proportions are enhanced in order to preserve the "grey world assumption" . If the level of the proportions is
  • the gamma correction functions which have been described above can be amplified or applied more specifically by means of the known vehicle colours.
  • d it is possible to make a good assumption about the range of the incident light.
  • information indicating whether the light is switched on can also be obtained from the vehicle data in order to improve the reliability of the
  • the invention can be applied not only to vehicles in road traffic but also to other image-evaluation

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Abstract

La présente invention se rapporte à un procédé et à un système de caméra permettant d'améliorer le contraste d'une image de caméra comprenant l'évaluation de la répartition de la luminosité de l'image et l'application à l'image d'une fonction de correction du contraste. Afin d'améliorer le contraste dans des conditions d'éclairage difficiles, on détermine la répartition de la luminosité dans l'espace tandis que la fonction de correction du contraste est modifiée en fonction de la répartition de la luminosité dans l'espace.
PCT/EP2009/004783 2009-07-02 2009-07-02 Procédé et système de caméra permettant d'améliorer le contraste d'une image de caméra WO2011000392A1 (fr)

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Application Number Priority Date Filing Date Title
PCT/EP2009/004783 WO2011000392A1 (fr) 2009-07-02 2009-07-02 Procédé et système de caméra permettant d'améliorer le contraste d'une image de caméra

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PCT/EP2009/004783 WO2011000392A1 (fr) 2009-07-02 2009-07-02 Procédé et système de caméra permettant d'améliorer le contraste d'une image de caméra

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102012011885A1 (de) * 2012-06-15 2013-12-19 Connaught Electronics Ltd. Verfahren zum optimierten Weißabgleich eines Bildes, Kamerasystem und Kraftfahrzeug
US20150035985A1 (en) * 2013-08-01 2015-02-05 Connaught Electronics Ltd. Method for activating and deactivating an image correction function, camera system and motor vehicle
EP2839662A1 (fr) * 2012-04-20 2015-02-25 Connaught Electronics Ltd. Procédé d'équilibre des blancs d'une image prenant en compte la coloration du véhicule automobile
EP2744694A4 (fr) * 2011-08-17 2015-07-22 Lg Innotek Co Ltd Caméra destinée à un véhicule
RU2643663C2 (ru) * 2012-03-26 2018-02-02 Конинклейке Филипс Н.В. Устройства и способы для кодирования и декодирования изображений с hdr на основании областей яркости
CN112949530A (zh) * 2021-03-12 2021-06-11 新疆爱华盈通信息技术有限公司 用于停车场巡检车的巡检方法与系统、巡检车
US11882367B2 (en) 2019-10-18 2024-01-23 Connaught Electronics Ltd. Image processing method for producing a high dynamic range image of a scene

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006121386A (ja) * 2004-10-21 2006-05-11 Canon Inc 撮像装置
US20060256384A1 (en) * 1997-06-09 2006-11-16 Seiko Epson Corporation Image processing apparatus, an image processing method, a medium on which an image processing control program is recorded, an image evaluation device, an image evaluation method and a medium on which an image evaluation program is recorded
US20070292045A1 (en) * 2006-06-12 2007-12-20 Nissan Motor Co., Ltd. Image processing apparatus and image processing method
JP2007336531A (ja) * 2006-05-17 2007-12-27 Sony Corp 画像補正回路、画像補正方法および画像表示装置

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060256384A1 (en) * 1997-06-09 2006-11-16 Seiko Epson Corporation Image processing apparatus, an image processing method, a medium on which an image processing control program is recorded, an image evaluation device, an image evaluation method and a medium on which an image evaluation program is recorded
JP2006121386A (ja) * 2004-10-21 2006-05-11 Canon Inc 撮像装置
JP2007336531A (ja) * 2006-05-17 2007-12-27 Sony Corp 画像補正回路、画像補正方法および画像表示装置
US20070292045A1 (en) * 2006-06-12 2007-12-20 Nissan Motor Co., Ltd. Image processing apparatus and image processing method

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2744694A4 (fr) * 2011-08-17 2015-07-22 Lg Innotek Co Ltd Caméra destinée à un véhicule
US10155476B2 (en) 2011-08-17 2018-12-18 Lg Innotek Co., Ltd. Camera apparatus of vehicle
RU2643663C2 (ru) * 2012-03-26 2018-02-02 Конинклейке Филипс Н.В. Устройства и способы для кодирования и декодирования изображений с hdr на основании областей яркости
US10057600B2 (en) 2012-03-26 2018-08-21 Koninklijke Philips N.V. Brightness region-based apparatuses and methods for HDR image encoding and decoding
EP2839662A1 (fr) * 2012-04-20 2015-02-25 Connaught Electronics Ltd. Procédé d'équilibre des blancs d'une image prenant en compte la coloration du véhicule automobile
DE102012011885A1 (de) * 2012-06-15 2013-12-19 Connaught Electronics Ltd. Verfahren zum optimierten Weißabgleich eines Bildes, Kamerasystem und Kraftfahrzeug
US20150035985A1 (en) * 2013-08-01 2015-02-05 Connaught Electronics Ltd. Method for activating and deactivating an image correction function, camera system and motor vehicle
EP2833618A3 (fr) * 2013-08-01 2015-02-11 Connaught Electronics Ltd. Procédé permettant d'activer et de désactiver une fonction de correction d'image, système de caméra et véhicule à moteur
US9762810B2 (en) * 2013-08-01 2017-09-12 Connaught Electronics Ltd. Method for activating and deactivating an image correction function, camera system and motor vehicle
US11882367B2 (en) 2019-10-18 2024-01-23 Connaught Electronics Ltd. Image processing method for producing a high dynamic range image of a scene
CN112949530A (zh) * 2021-03-12 2021-06-11 新疆爱华盈通信息技术有限公司 用于停车场巡检车的巡检方法与系统、巡检车
CN112949530B (zh) * 2021-03-12 2024-05-28 芯算一体(深圳)科技有限公司 用于停车场巡检车的巡检方法与系统、巡检车

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