Abstract: A UAV is provided to cancel background noise from audio data collected by the UAV. The UAV is provided with one or more background microphones in a proximity of one or more background noise-producing components. The UAV is also provided with one or more audio source collecting microphones. The audio data collected by the background microphones may be used to reduce or cancel interfering background noise from the audio signal detected by the audio source collecting microphone. The target audio may be captured or recorded with little or no background noise.

Abstract: An imaging system for adaptively generating panoramic images and methods for manufacturing and using same are provided. The system includes an imaging device configured to capture digital images at a plurality of image capture positions. The system further includes a processor configured to identify an overlapping portion of first and second images captured at respective first and second image capture positions, determine a stitching position quality measure for a plurality of stitching positions in the overlapping portion of the first and second images, and select a stitching position based on the determined stitching position quality measures of the plurality of stitching positions of the first and second images. The processor is also configured to stitch the first and second images together at the selected stitching position to generate a panoramic image and determine a third image capture position based on the stitching position quality measure.

Abstract: The present disclose provides a Bayer color filter array based high dynamic range video recording method and device. The method includes configuring different photosensitive times for exposure according to odd-numbered dual columns and even-numbered dual columns, and obtaining an image frame with different exposure values of the odd-numbered dual columns and even-numbered dual columns; decomposing the image frame into an underexposure image frame and an overexposure image frame, where underexposure dual columns and missing dual columns are alternatingly distributed in the underexposure image frame, and overexposure dual columns and missing dual columns are alternatingly distributed in the overexposure image frame. The method also includes acquiring recovered pixel values of pixel points of the missing dual columns in the underexposure image frame and the overexposure image frame; and merging the overexposure image frame and the underexposure image frame to obtain a high dynamic range frame.

Abstract: The present invention provides methods, systems, and apparatus for generating panoramic aerial images. An image capturing device is coupled to an unmanned aerial vehicle (UAVs) via a carrier configured to allow the image capturing device to rotate around one, two, or three axes relative to the UAV. To generate a panoramic image, the UAV is brought to hover or remain substantially stationary near a predetermined location. While the UAV is hovering over the predetermined position, the carrier causes the image capturing device to rotate around a first axis while stabilizing the image capturing device with respect to at least a second axis. As the image capturing device rotates, it captures a plurality of overlapping images. The plurality of images can be processed entirely onboard the UAV to generate a panoramic image without transmitting the plurality of images to a remote device.

Abstract: System and method can support an image processing device. The image processing device operates to obtain a first set of characterization values, which represents a first group of pixels that are associated with a denoising pixel in an image. Also, the image processing device can obtain a second set of characterization values, which represents a second group of pixels that are associated with a denoising reference pixel. Furthermore, the image processing device operates to use the first set of characterization values and the second set of characterization values to determine a similarity between the denoising pixel and the denoising reference pixel. Then, the image processing device can calculate a denoised value for the denoising pixel based on the determined similarity between the denoising pixel and the denoising reference pixel.

Abstract: A system for automatic focusing with a lens and methods for making and use the same are provided. When performing a focusing operation, a controller calculates a focus measure value for each lens position of a plurality of lens positions. The focus measure values are calculated based on each of the window evaluation values and a respective weight for image focusing windows within a set of image focusing windows. The controller then compares the calculated focus measure values of the plurality of lens positions in order to select an optimal lens position. The set of image focusing windows can be selected based on one or more sets of image focusing window selection rules derived from statistical data. In addition, the respective weights for image focusing windows can also be calculated based on the statistical data.

Abstract: A system and method for color correction is disclosed to reduce noise amplification during color correction. The method can comprise color correcting a noise evaluation image using a plurality of color correction parameters, determining a noise amplification metric by comparing the corrected noise evaluation image with the pre-correction noise evaluation image, and adjusting the plurality of color correction parameters based on the noise amplification metric.

Abstract: System and method can support an image processing device. The image processing device operates to obtain a first set of characterization values, which represents a first group of pixels that are associated with a denoising pixel in an image. Also, the image processing device can obtain a second set of characterization values, which represents a second group of pixels that are associated with a denoising reference pixel. Furthermore, the image processing device operates to use the first set of characterization values and the second set of characterization values to determine a similarity between the denoising pixel and the denoising reference pixel. Then, the image processing device can calculate a denoised value for the denoising pixel based on the determined similarity between the denoising pixel and the denoising reference pixel.

Abstract: Imaging systems having multiple optical modules are provided to achieve higher zoom ratio and better displaying effect. The FOVs or focal length ranges of the multiple optical modules may be designed to achieve a zoom ratio higher than either of the multiple optical modules and a Picture-in-Picture function. The gravity center of the imaging system may not be significantly varied during the zooming in and zooming out of the multiple optical modules.

Abstract: A system and method for calibrating a digital imaging device for color correction is disclosed. The method comprises obtaining an input color value and a reference color value for each of a plurality of color references, as well as a noise evaluation image having a color noise for evaluating noise reduction, the input color values and reference color values being in a non-linear color space. A plurality of color correction parameters are determined as optimized based on evaluating a fitness function in the non-linear color space. The non-linear color space can be a CIE L*a*b* color space. The fitness function can include a color correction error and a noise amplification metric so as to reduce noise amplification during color correction.

Abstract: Systems, methods, and devices for setting camera parameters are provided. In one aspect, a system for imaging a target object using an imaging device carried by a movable object comprises: one or more sensors configured to detect motion information for the movable object; and one or more processors configured to: receive, from the one or more sensors, the motion information for the movable object; determine, based on the motion information, a change in a spatial relationship between the movable object and the target object; and modify one or more parameters of the imaging device based on the determined change in the spatial relationship between the movable object and the target object such that the imaging device is focused on the target object.

Abstract: Methods and systems for evaluating a search area for encoding video are provided. The method comprises receiving video captured by an image capture device, the video comprising video frame components. Additionally, the method comprises receiving optical flow field data associated with the video frame component, wherein at least a portion of the optical flow field data is captured by sensors. The method also comprises determining a search area based on the optical flow field data.

Abstract: A system for image demosaicing and methods for manufacturing and using same. The image demosaicing system includes a lens, a mosaicing filter, an image sensor array and a processing module. The processing module is configured to perform adaptive demosaicing on a mosaiced image that was generated from sensed light that passed through the lens and mosaicing filter. The method of image demosaicing comprises interpolating values of unknown red, green and blue pixels in a horizontal and vertical direction and adaptively selecting one of the interpolation results for each pixel. The disclosed system and method provide for high quality image processing while operating at various Signal to Noise Ratios (SNRs) and require minimal computational time and overhead.

Abstract: A system for high dynamic range (HDR) imaging and methods for making and using same is disclosed. An HDR module in a camera initializes a set of lookup tables (LUTs) in YUV color space based on exposure configurations of a set of images taken as HDR imaging. The HDR module calculates weights of luminance Y components of the set of images in YUV color space. Based on the calculated weights, the HDR module blends the Y component of the set of images to generate blended Y components. The HDR module combines the blended Y components with corresponding UV components to generate a single image in YUV space. Thereby, the HDR module advantageously combines a set of images into a blended HDR image with only blending the Y component of the set of images.

Abstract: The present disclose provides a Bayer color filter array based high dynamic range video recording method and device. The method includes configuring different photosensitive times for exposure according to odd-numbered dual columns and even-numbered dual columns, and obtaining an image frame with different exposure values of the odd-numbered dual columns and even-numbered dual columns; decomposing the image frame into an underexposure image frame and an overexposure image frame, where underexposure dual columns and missing dual columns are alternatingly distributed in the underexposure image frame, and overexposure dual columns and missing dual columns are alternatingly distributed in the overexposure image frame. The method also includes acquiring recovered pixel values of pixel points of the missing dual columns in the underexposure image frame and the overexposure image frame; and merging the overexposure image frame and the underexposure image frame to obtain a high dynamic range frame.

Abstract: The present invention provides a method and apparatus for generating a high dynamic range image (HDRI). After acquiring a first illuminance diagram, a base layer and detail layers are extracted from the first illuminance diagram, where the base layer contains low frequency information of the first illuminance diagram and the detail layers contain high frequency information of the first illuminance diagram. The dynamic range of the base layer is then compressed while dynamic ranges of the detail layers remain uncompressed. Further, a second illuminance diagram is generated from the first illuminance diagram by fusing the base layer with the compressed dynamic range and the detail layers, the second illuminance diagram is mapped onto a plurality of preset color channels; and the images on the plurality of preset color channels are fused into the HDRI. Therefore, the detail information in the original illuminance diagram can be preserved.

Abstract: An image processing method includes capturing an initial image of a subject based on a preset initial exposure value, capturing a compensatory image of the subject based on a preset compensatory exposure value greater than the initial exposure value, calculating a synthesized pixel value at a pixel coordinate position based on a pixel value of an initial pixel at the pixel coordinate position in the initial image and a pixel value of a compensatory pixel at the pixel coordinate position in the compensatory image, and generating a captured image based upon the synthesized pixel value.

Abstract: System and method can support photography. A controller can configure a carrier to move an imaging device along a moving path. Furthermore, the controller can apply a time-dependent configuration on the imaging device, and use the imaging device for capturing a set of image frames along the moving path based on the one or more time-dependent parameters.

Abstract: System and method can support three-dimensional display. The system can receive a plurality of image frames, which are captured by an imaging device on a movable object. Furthermore, the system can obtain state information of the imaging device on the movable object, and use the state information to configure a pair of image frames based on the plurality of image frames for supporting a three-dimensional first person view (FPV). Additionally, an image frame selected from the plurality of image frames can be used for a first image frame in the pair of image frames.

Abstract: System and method can support an image processing device. The image processing device operates to obtain a first set of characterization values, which represents a first group of pixels that are associated with a denoising pixel in an image. Also, the image processing device can obtain a second set of characterization values, which represents a second group of pixels that are associated with a denoising reference pixel. Furthermore, the image processing device operates to use the first set of characterization values and the second set of characterization values to determine a similarity between the denoising pixel and the denoising reference pixel. Then, the image processing device can calculate a denoised value for the denoising pixel based on the determined similarity between the denoising pixel and the denoising reference pixel.