Provided is a method and system that includes an imaging device to be disposed in a lighting fixture to capture images, a remote computing device in communication with the imaging device, and comprising at least one processor. The processor is capable of processing data related to images from the at least one imaging device and from a satellite imagery system, performing comparison operation by detecting a first set of points of interest in an image from the at least one imaging device and corresponding second set of points of interest in an image of a same area from the satellite imagery system, and calculating a homography matrix by matching the first set of points of interests in the image from the at least one imaging device and the second set of points of interest in the image from the satellite imagery system, to determine latitude and longitude coordinates of the image from the imaging device.

Aspects of the subject disclosure may include, for example, obtaining image content over a communication network, determining a predicted viewpoint of a user associated with the image content, and adjusting the image content to equirectangular image content according to the predicted viewpoint. Further aspects can include downscaling the equirectangular image content according to a display capability of a mobile device resulting in a downscaled equirectangular image content, cropping the downscaled equirectangular image content resulting in a cropped equirectangular image content, and providing, over the communication network, the cropped equirectangular image content to the mobile device. Other embodiments are disclosed.

The present disclosure relates to an image processing apparatus and method for transforming image data of a spherical coordinate system corresponding to image data of a planar coordinate system without transforming the image data of the planar coordinate system, and stitching the transformed image data of the spherical coordinate system to the image data of the planar coordinate system.

Electronic devices are often equipped with a camera for capturing video content and/or a display for displaying video content. However, amateur users often capture video content without regard to composition, framing, or camera movement, resulting in video content that can be jarring or confusing to viewers. There is a need to automate the processing and presentation of video content in an aesthetically pleasing manner. The embodiments described herein provide a method of automatically cropping video content for presentation on a display.

An image creation unit of a server creates and stores a plurality of phase images or the like having different resolutions on the basis of holographic data collected by a measuring terminal. In response to an image transmission request according to an operation, an image transmission processing unit of the server extracts data of an image corresponding to an observation range after the movement from an image of an appropriate resolution and transmits the data to the browsing terminal. In the browsing terminal, a display image is formed by overlaying a high-resolution phase image corresponding to only an observation range to be displayed on low-resolution phase image of an observation target area.

A method and system for generating an output image from a plurality, N, of corresponding input image channels is described. A Jacobian matrix of the plurality of corresponding input image channels is determined. The principal characteristic vector of the outer product of the Jacobian matrix is calculated. The sign associated with the principal characteristic vector is set whereby an input image channel pixel projected by the principal characteristic vector results in a positive scalar value. The output image as a per-pixel projection of the input channels in the direction of the principal characteristic vector is generated.

An image processing method determines a geometric transform of a suspect image by efficiently evaluating a large number of geometric transform candidates in environments with limited processing resources. Processing resources are conserved by using complementary methods for determining a geometric transform of an embedded signal. One method excels at higher geometric distortion, and specifically, distortion caused by greater tilt angle of a camera. Another method excels at lower geometric distortion, for weaker signals. Together, the methods provide a more reliable detector of an embedded data signal in image across a larger range of distortion while making efficient use of limited processing resources in mobile devices.

Provided is a method and system that includes an imaging device to be disposed in a lighting fixture to capture images, a remote computing device in communication with the imaging device, and comprising at least one processor. The processor is capable of processing data related to images from the at least one imaging device and from a satellite imagery system, performing comparison operation by detecting a first set of points of interest in an image from the at least one imaging device and corresponding second set of points of interest in an image of a same area from the satellite imagery system, and calculating a homography matrix by matching the first set of points of interests in the image from the at least one imaging device and the second set of points of interest in the image from the satellite imagery system, to determine latitude and longitude coordinates of the image from the imaging device.

A method of adjusting texture coordinates based on control regions in a panoramic image is disclosed. The method comprises determining warping coefficients of a plurality of control regions in a panoramic image; retrieving two selected warping coefficients out of the warping coefficients for each of a plurality of camera images with respect to each vertex from a first vertex list according to two coefficient indices for each camera image in its data structure; calculating an interpolated warping coefficient for each camera image with respect to each vertex according to the two selected warping coefficients and a coefficient blending weight for each camera image in its data structure; and, calculating modified texture coordinates in each camera image for each vertex according to the interpolated warping coefficient and original texture coordinates for each camera image in its data structure to form a second vertex list.

A style of a digital image is transferred to another digital image of arbitrary resolution. A high-resolution (HR) content image is segmented into several low-resolution (LR) patches. The resolution of a style image is matched to have the same resolution as the LR content image patches. Style transfer is then performed on a patch-by-patch basis using, for example, a pair of feature transformswhitening and coloring. The patch-by-patch style transfer process is then repeated at several increasing resolutions, or scale levels, of both the content and style images. The results of the style transfer at each scale level are incorporated into successive scale levels up to and including the original HR scale. As a result, style transfer can be performed with images having arbitrary resolutions to produce visually pleasing results with good spatial consistency.