Abstract: Systems and methods for altering colors of pixels of images produced by cameras using a lens. A plurality of generated images are received, and color channel values and luminance values of image pixels are determined. Benchmark U-color thresholds and V-color thresholds are established based on the color channels and luminance associated with the pixels. A first image generated using a first lens of a first camera is received. U-color values and V-color values associated with first pixels of the first image are determined. A uniformity score associated with the first lens is received. The benchmark U-color and V-color thresholds are altered based on the uniformity score. The U-color values and V-color values of the first pixels are corrected in response to the U-color values being within the altered U-color thresholds and the V-color values being within the altered V-color thresholds.

Abstract: A composite top view of an area surrounding a vehicle is generated utilizing image harmonization and proximity sensor data. Images from various vehicle cameras are received, wherein at least two of the cameras can see the same portion of the environment in an overlapping region. The images are segmented into segments. The overlapping regions include some of the segments of one image and some of the segments of another region to define overlapping segments. Sensor data is received from a plurality of proximity sensors, wherein the sensor data indicates a location of an object outside of the vehicle. The color and/or brightness of the images are harmonized based at least in part on the sensor data. In particular embodiments, weights are placed on the color and/or brightness of the overlapping segments associated with the location of the object. Or these overlapping segments can be removed from the harmonization.

Abstract: Methods and systems for generating a top view of an area surrounding the vehicle. Images are received from a plurality of vehicle cameras configured to view respective regions of ground outside of the vehicle. Portions of at least some of the regions overlap with portions of another of the regions, defining overlapping portions. Each image is segmented into a respective plurality of segments, wherein the overlapping portions include some of the segments of one image and some of the segments of another image to define overlapping segments. A first harmonization model harmonizes the images based on brightness or color values within the overlapping segments. When an angular orientation of at least one of the plurality of vehicle cameras relative to the ground exceeds a threshold, a second harmonization model is executed in order to account for occlusions or lack of image data when the camera is angled.

Abstract: Systems and methods for altering colors of pixels of images produced by cameras using a lens. A plurality of generated images are received, and color channel values and luminance values of image pixels are determined. Benchmark U-color thresholds and V-color thresholds are established based on the color channels and luminance associated with the pixels. A first image generated using a first lens of a first camera is received. U-color values and V-color values associated with first pixels of the first image are determined. A uniformity score associated with the first lens is received. The benchmark U-color and V-color thresholds are altered based on the uniformity score. The U-color values and V-color values of the first pixels are corrected in response to the U-color values being within the altered U-color thresholds and the V-color values being within the altered V-color thresholds.

Abstract: A composite top view of an area surrounding a vehicle is generated utilizing image harmonization and proximity sensor data. Images from various vehicle cameras are received, wherein at least two of the cameras can see the same portion of the environment in an overlapping region. The images are segmented into segments. The overlapping regions include some of the segments of one image and some of the segments of another region to define overlapping segments. Sensor data is received from a plurality of proximity sensors, wherein the sensor data indicates a location of an object outside of the vehicle. The color and/or brightness of the images are harmonized based at least in part on the sensor data. In particular embodiments, weights are placed on the color and/or brightness of the overlapping segments associated with the location of the object. Or these overlapping segments can be removed from the harmonization.

Abstract: A method for reducing temporal noise in an image sequence by a camera of an assistance system of a motor vehicle by an electronic computing device. The method includes capturing a first image and a second image of the image sequence of an environment of the motor vehicle by the camera at a first point and a second point in time. Furthermore, determining at least one feature in the second image and determining of pixels associated with the at least one feature in the second image by the feature capturing module. Moreover, generating a weighting map comprising a weight value for each pixel of the second image by an adaptive motion estimation module. Lastly, reducing the temporal noise by blending pixels of the first image with pixels of the second image in dependence on the generated weighting map by a blending module.

Abstract: A method for reducing a color shift of image pixels of an image for a motor vehicle captured by a camera, a computer program product and a control device for the vehicle are disclosed. For the respective image pixel of the image, the method involves determining a color information, which describes a color of the image pixel, checking whether the determined color information is larger than a minimum color information and smaller than a maximum color information, wherein the minimum and maximum color information delimit a color information range, in which reference image pixels describing a reference object sway. When the checking is successful, calculating a corrected color information in consideration of the determined color information and a correction factor and providing the calculated corrected color information instead of the determined color information, wherein the corrected color information in comparison to the determined color information has a reduced color shift.

Abstract: The invention relates to a method for generating an output image with a predefined target view showing a motor vehicle (1) and an environmental region (4) of the motor vehicle (1) based on at least partially overlapping raw images (RC1, RC2, RC3, RC4) captured by at least two vehicle-side cameras (5a, 5b, 5c, 5d), comprising the steps of: specifying respective camera-specific pixel density maps (PDM1a, PDM1b, PDM2a, PDM2b), which each describe an image-region dependent distribution of a number of pixels of the raw image (R1 to R4) captured by the associated camera (5a to 5d) contributing for the generation of the output image, spatially adaptive filtering of the raw images (RC1 to RC4) based on the pixel density map (PDM1a to PDM2b) specific to the associated camera (5a to 5d), which indicates an image region-dependent extent of the filtering, identifying mutually corresponding image areas (B1a, B1b, B2a, B2b, B3a, B3b, B4a, B4b) in the at least partially overlapping raw images (RC1 to RC4) of the at least

Abstract: A camera device for a motor vehicle includes an image sensor to provide a raw image (R) of an environment of the camera device. Additionally, an image processing device generates an output image (I) from the raw image (R) by means of a spreading function of a histogram spreading. The spreading function generates from a respective input pixel value (Li) of each pixel of the raw image (R) each one output pixel value (Lo) of a corresponding pixel of the output image (I). Furthermore, the histogram spreading may be adapted to the capturing situation. At least one parameter value (S, G) of the camera device depending on a brightness (B1, B2) of the environment is acquired and a limit value (L) for the output pixel values (Lo) is set in the spreading function depending on the at least one acquired parameter value (S, G).

Abstract: The invention relates to a method for adapting a brightness (28) of a high-contrast image (20, 22) of an environmental region (9) of a motor vehicle (1) including the following steps of: a) capturing a first image with a first camera parameter of a camera system (2) of the motor vehicle (1) and a second image with a second camera parameter of the camera system (2) by means of the camera system (2), b) generating a first high-contrast image (20) of the environmental region (9) with the first image and the second image, c) determining a high-contrast brightness value (23) of the first high-contrast image (20), d) comparing the high-contrast brightness value (23) to a predetermined high-contrast target brightness value, e) adapting the first high-contrast image (20) depending on the comparison according to step d), f) determining a first brightness value of the first image and/or a second brightness value of the second image, g) comparing the first brightness value to a first target brightness value (26) and/or

Abstract: The invention relates to methods for operating a camera device (4) for a motor vehicle (3). An image sensor (5) of the camera device (4) provides a raw image (R) of an environment (8) of the camera device (4). An image processing device (6) generates an output image (I) from the raw image (R) by means of a spreading function (13) of a histogram spreading (12). The spreading function (13) generates from a respective input pixel value (Li) of each pixel of the raw image (R) each one output pixel value (Lo) of a corresponding pixel of the output image (I). It is the object of the invention to adapt the histogram spreading (12) to the capturing situation. At least one parameter value (S, G) of the camera device (4) depending on a brightness (B1, B2) of the environment (8) is acquired and a limit value (L) for the output pixel values (Lo) is set in the spreading function (13) depending on the at least one acquired parameter value (S, G).