Abstract: A method includes receiving one or more panoramic image processing parameters from a remote terminal, controlling a carrier to rotate an image capturing device about a first axis of the carrier while causing the image capturing device to capture a plurality of images based at least in part on the one or more panoramic image processing parameters, and stabilizing the image capturing device against motions with respect to a second axis or a third axis of the carrier while the image capturing device is rotating about the first axis of the carrier. The image capturing device is coupled to an unmanned aerial vehicle (UAV) via the carrier.

Abstract: An image noise calibration apparatus includes a processor. The processor acquires raw image data output by an image sensor. The image sensor includes an image sensitive unit array, and the raw image data is output by the image sensitive unit array in an optical black state. The processor further determines fixed pattern noise calibration data of the image sensor based on the raw image data output by the image sensitive unit array. The fixed pattern noise calibration data is used for noise reduction of the image sensitive unit array, and the number of the fixed pattern noise calibration data is less than the number of image sensitive units in the image sensor.

Abstract: A method of imaging on a mobile platform includes exposing an imaging device mounted aboard the mobile platform at a plurality of positions of a component of the mobile platform to obtain images, determining, using the images, allowed positions of the component that do not obstruct a field-of-view of the imaging device, and controlling the imaging device according to the allowed positions to avoid imaging the component.

Abstract: A method includes obtaining a dynamic range representation of an image including multiple color channels. The dynamic range representation includes dynamic range information of pixels of the image in the color channels. The method further includes decomposing the dynamic range representation into a smooth portion, a color portion, and a detail portion. The smooth portion includes low frequency information of the pixels in the color channels. The color portion includes color intensity information of the pixels in the color channels. The detail portion includes high frequency information of the pixels in the color channels. The method also includes adjusting the smooth portion, the color portion, and the detail portion, respectively, to obtain an adjusted smooth portion, an adjusted color portion, and an adjusted detail portion, and combining the adjusted smooth portion, the adjusted color portion, and the adjusted detail portion to generate an output image.

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: 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 computer-implemented method for color correction includes determining a peak signal-to-noise ratio (PSNR) for a noise evaluation image, determining a corrected PSNR for a corrected noise evaluation image, determining a downsampled PSNR for a downsampled noise evaluation image obtained by downsampling the noise evaluation image, determining a downsampled corrected PSNR for a downsampled corrected noise evaluation image obtained by downsampling the corrected noise evaluation image, and determining a noise amplification metric based on the PSNR, the corrected PSNR, the downsampled PSNR, and the downsampled corrected PSNR.

Abstract: An imaging system includes a first optical module including a first image sensor, a second optical module comprising a second image sensor, and an image processor. The first optical module has a first focal length range. The second optical module has a second focal length range. The first focal length range and the second focal length range are different. The image processor is configured to receive image data for a first image from the first optical module and/or image data for a second image from the second optical module and generate data to show the first image and/or the second image within a display.

Abstract: An imaging system includes one or more sensors configured to detect movement of a movable object carrying an imaging device and one or more processors individually or collectively configured to set one or more parameters of the imaging device such that the imaging device is focused on a target object when the movable object is in a first spatial disposition, detect a movement of the movable object from the first spatial disposition to a second spatial disposition through the one or more sensors, and modify the one or more parameters of the imaging device in response to the detected movement such that the imaging device is focused on the target object when the movable object is in the second spatial disposition.

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 method for generating panoramic images includes controlling a carrier to rotate an image capturing device around at least a first axis of the carrier, controlling the carrier to stabilize the image capturing device against vibrations or disturbances with respect to a second axis of the carrier or a third axis of the carrier while the image capturing device is rotating around the first axis, causing 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 by stitching two or more of the plurality of images. The image capturing device is coupled to an unmanned aerial vehicle (UAV) via the carrier, and the carrier is coupled to the UAV via one or more damping members configured to reduce motions transmitted to the carrier by the UAV.

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 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 configured to capture a first image from the first light beam focused by the first lens module onto the first sensor, a second sensor 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 generate a combined image based on the first image and the second image. The first image has a first field of view and the second image has a second field of view different from the first field of view.

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: 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: 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 method of image processing includes obtaining depth information respectively corresponding to one or more objects in an image frame captured by an imaging system based on spatial configuration of the imaging system, calculating one or more rendering parameters associated with one of the one or more objects in the image frame based on at least the depth information of the one or more objects, and rendering the image frame using the one or more rendering parameters to obtain a processed image frame. The processed image frame includes an in-focus region and an out-of-focus region relative to the one of the one or more objects.

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: A method and an apparatus for adjusting installation flatness of a lens in real time are provided. The method comprises: acquiring an image captured by a camera in real time, where the image comprises at least two groups of testing charts regarding different positions; pre-processing the image to obtain each group of testing charts by separation; calculating and displaying, based on each group of testing charts, a real-time resolution value of a camera photosensitive surface to each group of testing charts in real time; and adjusting the installation angle of the optical axis of the camera lens relative to the camera photosensitive surface in real time based on the real-time resolution value of the camera photosensitive surface to each group of testing charts.

Abstract: A method for generating a high dynamic range image (HDRI) includes acquiring a first illuminance diagram, generating a second illuminance diagram from the first illuminance diagram by modifying a dynamic range of at least a portion of the first illuminance diagram, and generating the HDRI based on the second illumination diagram. The first illuminance diagram is obtained based on a camera response function and an illuminance logarithm obtained based on a plurality of images having different exposure conditions.