A vehicular vision system includes a rearward-viewing camera and a forward-viewing camera disposed at a vehicle. Image data captured by the cameras is provided to the electronic control unit. The electronic control unit sends respective control data to the cameras, and the respective sent control data is stored in respective memory of the cameras. With the respective sent control data stored in the respective memory of the cameras, the electronic control unit sends a trigger signal to the cameras. Responsive to the sent trigger signal, the cameras load operational parameters of the respective stored control data into respective image sensors of the cameras so that the operational parameters of the respective image sensors of the cameras are synchronized. With the operational parameters of the respective image sensors of the cameras synchronized, image data is captured by the respective image sensors and is sent to the electronic control unit.

The present application provides an electronic device and an in-screen optical detection assembly. The electronic device can detect an ambient color temperature on a screen side. The electronic device includes a middle frame, a screen, a circuit board, and a color temperature detection assembly, where the screen includes a display and a cover plate located on one side of the display; the middle frame is located between the display and the circuit board and provided with a first through hole; the optical detection assembly includes a light shield body and a light sensor, where the light shield body is provided with a light hole, a first end of the light shield body is connected to the circuit board, and a second end of the light shield body passes through the first through hole and extends to one side of the screen facing the middle frame; and the light sensor is disposed on the circuit board and located in the light hole.

An information processing apparatus acquires imaging parameters of a first imaging apparatus and a second imaging apparatus, and based on the imaging parameters, determines a number of first images to be captured by the first imaging apparatus and a number of second images to be captured by the second imaging apparatus. Further, the information processing apparatus acquires first color information included in the first images and second color information included in the second images, and based on the first color information and the second color information, generates color correction information for correcting a difference in color between the first and second images.

An information processing apparatus acquires imaging parameters of a first imaging apparatus and a second imaging apparatus, and based on the imaging parameters, determines a number of first images to be captured by the first imaging apparatus and a number of second images to be captured by the second imaging apparatus. Further, the information processing apparatus acquires first color information included in the first images and second color information included in the second images, and based on the first color information and the second color information, generates color correction information for correcting a difference in color between the first and second images.

Scene-based automatic white balance correction may be performed by obtaining an input image. A histogram may be computed from an image thumbnail. The scene-based automatic white balance correction may include classifying a scene. The scene-based automatic white balance correction may include learning a first filter and a second filter. The first filter and the second filter may be learned from one or several different instances of the raw image thumbnail, the augmented image thumbnail, the scene classification, or any combination thereof. The scene-based automatic white balance correction may include applying the filter to the histogram to determine white balance correction coefficients and obtain a processed image.

Scene-based automatic white balance correction may be performed by obtaining an input image. A histogram may be computed from an image thumbnail. The scene-based automatic white balance correction may include classifying a scene. The scene-based automatic white balance correction may include learning a first filter and a second filter. The first filter and the second filter may be learned from one or several different instances of the raw image thumbnail, the augmented image thumbnail, the scene classification, or any combination thereof. The scene-based automatic white balance correction may include applying the filter to the histogram to determine white balance correction coefficients and obtain a processed image.

An image correction method for correcting multiple original images captured under illumination by multiple different light source colors in generating a composite image by superposing the original images, includes obtaining a correction amount for correcting a position of a fiducial mark recognized from a reference image of a specific light source color in reference images of the multiple different light source colors; obtaining correction amounts for correcting positions of the fiducial mark recognized from the reference images of other light source colors than a specific light source color to the reference position in the reference image of the specific light source color; and when the original images are captured, correcting collectively distortion aberration and chromatic aberration of the original images of the multiple different light source colors using the correction amounts associated with the multiple different light source colors.

An image correction method for correcting multiple original images captured under illumination by multiple different light source colors in generating a composite image by superposing the original images, includes obtaining a correction amount for correcting a position of a fiducial mark recognized from a reference image of a specific light source color in reference images of the multiple different light source colors; obtaining correction amounts for correcting positions of the fiducial mark recognized from the reference images of other light source colors than a specific light source color to the reference position in the reference image of the specific light source color; and when the original images are captured, correcting collectively distortion aberration and chromatic aberration of the original images of the multiple different light source colors using the correction amounts associated with the multiple different light source colors.

An electronic device is provided. The electronic device includes a first camera, a display, a second camera disposed below the display, and at least one processor, wherein the at least one processor is configured to acquire first image data and first environment information associated with the first image data by using the first camera, acquire second image data and second environment information associated with the second image data by using the second camera, determine whether to correct a correction value related to the second camera based on the second image data, the correction value including at least one of a white balance correction value for correcting white balance of the second camera or a lens shading correction value for correcting lens shading of the second camera, identify a similarity between the first environment information and the second environment information in response to determining to correct the correction value related to the second camera, and correct the correction value related to the second camera by using at least the similarity based on the first image data.

An electronic device is provided. The electronic device includes a first camera, a display, a second camera disposed below the display, and at least one processor, wherein the at least one processor is configured to acquire first image data and first environment information associated with the first image data by using the first camera, acquire second image data and second environment information associated with the second image data by using the second camera, determine whether to correct a correction value related to the second camera based on the second image data, the correction value including at least one of a white balance correction value for correcting white balance of the second camera or a lens shading correction value for correcting lens shading of the second camera, identify a similarity between the first environment information and the second environment information in response to determining to correct the correction value related to the second camera, and correct the correction value related to the second camera by using at least the similarity based on the first image data.