Disclosed is an image fusion method and apparatus. The fusion method includes detecting first feature points of an object in a first image frame from the first image frame; transforming the first image frame based on the detected first feature points and predefined reference points to generate a transformed first image frame; detecting second feature points of the object in a second image frame from the second image frame; transforming the second image frame based on the detected second feature points and the predefined reference points to generate a transformed second image frame; and generating a combined image by combining the transformed first image frame and the transformed second image frame.

A set of input images from satellites (or other remote sensors) can be orthorectified and stitched together to create a mosaic. If the resulting mosaic is not of suitable quality, the input images can be adjusted and the processes of orthorectifying and creating the mosaic can be repeated. However, orthorectifying and creating the mosaic uses a large amount of computational resources and takes a lot of time. Therefore, performing numerous iterations is expensive and sometimes not practical. To overcome these issues, it is proposed to generate an indication of accuracy of the resulting mosaic prior to orthorectifying and creating the mosaic by accessing a set of points in the plurality of input images, projecting the points to a model, determining residuals for the projected points, and generating the indication of accuracy of the orthorectified mosaic based on the determined residuals.

A method and device for automatically generating residential building plan, comprises: obtaining the standard plans of the residential buildings in each geographical region, analyzing the standard plans to obtain information on the construction area, residential unit area, unit layout, unit plan outline and functional composition and dimension corresponding to each of the standard plans as original training data; conducting training with original training data according to each geographical region in order to establish the residential building plan generative adversarial network model; receiving constraints and objective such as the target construction area, target residential unit area, target unit plan outline and target unit layout of the target residential building, generating residential unit plan model with functional zones based on the generative adversarial network model; denoising and trimming the residential unit plan model to obtain defined geometric information of residential building plan.

Systems, computer-implemented methods, apparatus and/or computer program products are provided that facilitate improving the accuracy of global positioning system (GPS) coordinates of indoor photos. The disclosed subject matter further provides systems, computer-implemented methods, apparatus and/or computer program products that facilitate generating exterior photos of structures based on GPS coordinates of indoor photos.

In a method for generating combined image data based on first magnetic resonance (MR) data and second MR data, the first MR data and the second MR data are provided, the first MR data having been generated by a first actuation of a magnetic resonance device from an examination area of an examination object using a first sequence module, and the second MR data having been generated by a second actuation of the magnetic resonance device from the examination area of the examination object using the first sequence module, the first MR data and the second MR data are registered to one another to generate first registered MR data and second registered MR data; the first registered MR data and the second registered MR data are statistically combined to generate combined image data, and the combined image data is provided as an output in electronic form as a data file.

Disclosed are systems and methods for performing an auto-setup of a smile design for a patient using a digital orthodontics model. A method can include accessing, by a computer system, a digital orthodontics model for a patient and an image of the patient showing the patient's existing teeth, accessing orthodontics rules with permissible degrees of movement for each tooth, determining, based on the rules, tooth movements along an arch form defined in the model to achieve a desired teeth arrangement for the patient, selecting a set of veneers from amongst sets of veneers to achieve the desired teeth arrangement based on the tooth movements, overlaying the digital orthodontics model with teeth of the selected set, augmenting the image of the patient's teeth with the model having the teeth of the selected set, and returning at least the augmented image.

In a magnetic resonance method and apparatus for determining a characteristic of an organ, a magnetic resonance sequence is executed in order to acquire temporally resolved magnetic resonance data pertaining to the organ. The magnetic resonance sequence includes at least one tagging module, which generates a sub-visual tag of the magnetic resonance data. The characteristic of the organ is determined in a processor using the sub-visual tag.

A method and apparatus of processing and displaying images captured using an in vivo capsule camera are disclosed. One or more overlapped areas between a target image and each image in a neighboring image group are determined, which comprises at least two neighboring images around the target image. Marked pixels in the target image are then determined, where a pixel in the target image is designated as a marked pixel if the pixel is within an overlapped area between the target image and at least one neighboring image. If the total number of the marked pixels in the target image exceeds a threshold and the number of the marked pixels associated with the overlapped area(s) between the target image and any image in the neighboring image group is below the threshold, the target image is excluded from a set of images to be displayed on a display device.

A system receives digital images of a geographic location, associates each digital image with ground control points in a set of reference stereo images, and associates each digital image to each other digital image via image to image tiepoints. The system updates a geometry of each image via a bundle adjustment, and uses a prioritized stacking order to establish piecewise linear seam lines between each of the images. The system finally builds a prioritized map in a mosaic space specifying the source image pixels that are used in each region of the output mosaic, and forms the mosaic image using the prioritized map.

Automated three-dimensional (3D) building model estimation is disclosed. In an embodiment, a method comprises: obtaining, using one or more processors, an aerial image of a building based on an input address; obtaining, using the one or more processors, three-dimensional (3D) data containing the building based on the input address; pre-processing the aerial image and 3D data; reconstructing, using the one or more processors, a 3D building model from the pre-processed image and 3D data, the reconstructing including: predicting, using instance segmentation, a mask for each roof face; converting each roof face into a two-dimensional (2D) polygon; and projecting each 2D polygon into a 3D polygon representing the 3D building model.