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 supporting imaging includes an imaging device configured to capture a plurality of images for a substantially same scene using respective imaging configurations, a stabilization device configured to stabilize the imaging device on a mobile platform during the capturing of the plurality of images, and a controller communicating with at least one of the imaging device or the stabilization device and configured to control an operation of the mobile platform.

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: Provided is a method of correcting a defective pixel of a digital image. In the method, the defective pixels are pre-corrected. The similarities of normal pixels and each defective pixel are calculated. The weight of each normal pixel to each defective pixel is calculated based on the similarities of the normal pixels and each defective pixel. The weight of each normal pixel to each defective pixel is normalized. The normalized weighted values of the normal pixels to each defective pixel are weighted summed to obtain the corrected pixel value of each defective pixel.

Abstract: A method of video synchronization includes comparing image data from a reference frame sequence with corresponding image data of a search frame sequence and aligning the search frame sequence with the reference frame sequence based on the comparing.

Abstract: A system for focusing an imaging device according to a focal distance setting and methods for making and using same. The focal distance setting can be an infinite focal distance setting for objects that are far away from the imaging device. Focusing of the imaging device can be triggered by activation of a button for “one-touch” rapid focusing. The focusing, for example, can be triggered at a terminal that is distal from the imaging device through an app and suitable user interface. The focal distance setting can be determined by interaction via the app, which can present a prompt to direct the imaging device to an object at a suitable distance. Once determined, the focal distance setting can be stored and later retrieved for rapid focusing. The present system and methods advantageously can be used aboard a mobile platform such as an unmanned aerial vehicle.

Abstract: A computer-implemented method for color correction includes obtaining a noise evaluation image by adding noise to a noise-free image, color correcting the noise evaluation image using a plurality of color correction parameters, color correcting the noise-free image using the plurality of color correction parameters, determining a noise amplification metric at least by comparing the corrected noise evaluation image with the corrected noise-free image, and adjusting the plurality of color correction parameters based on the noise amplification metric.

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: A system includes an optical element configured to separate light into a first light beam and a second light beam, a first lens module configured to focus the first light beam, a second lens module configured to focus the second light beam, a first sensor having a first sensor size and configured to capture a first image from the first light beam focused by the first lens module onto the first sensor, a second sensor having a second sensor size different from the first sensor size and configured to capture a second image from the second light beam focused by the second lens module onto the second sensor, and one or more processors configured to modify the first image or the second image based on the first sensor size and the second sensor size to generate a modified image and generate a combined image based on the modified image.

Abstract: Systems and methods can support a data processing apparatus. The data processing apparatus can include a data processor that is associated with a data capturing device on a stationary object and/or a movable object. The data processor can receive data in a data flow from one or more data sources, wherein the data flow is configured based on a time sequence. Then, the data processor can receive a control signal, which is associated with a first timestamp, wherein the first timestamp indicates a first time. Furthermore, the data processor can determine a first data segment by applying the first timestamp on the data flow, wherein the first data segment is associated with a time period in the time sequence that includes the first time.

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: Provided is a method of correcting a defective pixel of a digital image. In the method, the defective pixels are pre-corrected. The similarities of normal pixels and each defective pixel are calculated. The weight of each normal pixel to each defective pixel is calculated based on the similarities of the normal pixels and each defective pixel. The weight of each normal pixel to each defective pixel is normalized. The normalized weighted values of the normal pixels to each defective pixel are weighted summed to obtain the corrected pixel value of each defective pixel.

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: An image processing method includes obtaining an acquired image captured by an image acquisition device and obtaining vibration information associated with the acquired image and generated while the image acquisition device capturing the acquired image. The vibration information includes an angle of vibration. The method further includes performing a distortion correction to the acquired image to obtain a distortion-corrected image based upon the vibration information and a preset distortion correction parameter, and determining a target image from the distortion-corrected image based upon the vibration information.

Abstract: Systems and methods can support a data processing apparatus. The data processing apparatus can include a data processor that is associated with a data capturing device on a stationary object and/or a movable object. The data processor can receive data in a data flow from one or more data sources, wherein the data flow is configured based on a time sequence. Then, the data processor can receive a control signal, which is associated with a first timestamp, wherein the first timestamp indicates a first time. Furthermore, the data processor can determine a first data segment by applying the first timestamp on the data flow, wherein the first data segment is associated with a time period in the time sequence that includes the first time.

Abstract: Imaging systems having multiple optical modules are provided. The FOVs, focal lengths, and/or sensors of the multiple optical modules may be designed to generate high quality images and images with arbitrary magnifications.

Abstract: An unmanned aerial vehicle (UAV) with audio filtering components includes a background noise-producing component, a background microphone, and a noise emitter. The background noise-producing component is configured to produce a background noise. The background microphone is positioned within a proximity sufficiently close to collect interfering noise from the background noise producing component. The background microphone is configured to collect audio data including the background noise. The noise emitter is disposed within a proximity sufficiently close to the background noise-producing component to reduce the interfering noise. The noise emitter is configured to emit an audio signal having a reverse phase of the audio data collected by the background microphone.

Abstract: A method for generating panoramic aerial images includes controlling a carrier to rotate an image capturing device by a predetermined angle of rotation around a first axis of the carrier. The image capturing device is coupled to an unmanned aerial vehicle (UAV) via the carrier and the carrier is configured to permit the image capturing device to rotate around at least the first axis and a second axis. The method further includes controlling the carrier to stabilize the image capturing device with respect to at least the second axis while the image capturing device is rotating around the first axis, by controlling one or more actuator members of the carrier. The method also includes controlling the image capturing device to capture a plurality of successive images while the image capturing device is rotating around the first axis and generating a panoramic image based on the captured plurality of images.

Abstract: A system for processing a video obtains a prediction table for a reference frame of the video and codes one or more target frames of the video based on the prediction table. The prediction table is a Huffman table of difference values for reference pixels of the reference frame. The difference value for a reference pixel is determined based on an actual value of the reference pixel and a prediction value determined based on respective pixel values of one or more pixels adjacent to the reference pixel. The one or more target frames are coded based on the Huffman table of the reference frame and prediction values of the one or more target frames.

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.