Microsoft Technology Licensing, LLC

Christian Markus Maekelae

Michael Bleyer

Christopher Douglas Edmonds

Raymond Kirk Price

Paul Lee

Techniques for performing image alignment between a first image generated by a first camera and a second image generated by a second camera are disclosed. The image alignment is performed using staggered feature extraction in which a set of features are reused to align the second image with the first image. A first set of features are identified from within the first image, and a second set of features, which were previously detected within the second image, are accessed. The second set of features were previously used at least once to perform a previous image alignment operation. A current image alignment operation is performed by using the first set of features and by reusing the second set of features to align the first image with the second image.

Image alignment using staggered feature extraction

A system for facilitating dark current compensation by weighted filtering is configurable to (i) receive an input dark current image; (ii) generate a corrected dark current image at least by scaling pixel values of the input dark current image based upon ambient light conditions; and generate a weight map comprising a weight value for each pixel of the corrected dark current image. For each pixel of the corrected dark current image, the weight value of the weight map may be based upon a light level of the pixel of the corrected dark current image. The system is also configurable to generate an output image by utilizing the weight map to filter an input image.

Systems and methods for facilitating dark current compensation by weighted filtering

A system for modifying a dark current image is configurable to receive an input image depicting a dark current state for one or more pixels of the input image, The dark current state for one or more pixels of the input image comprises one of: a faulty state or a non-faulty state. The system is configurable to partition the input image into a plurality of partitions and generate an updated input image by imposing at least one quantity constraint or at least one severity constraint to the plurality of partitions in association with at least one type of dark current state.

Systems and methods for selectively constraining and implementing cross talk templates for dark current images

Techniques to temporally filter images via a filtering weight computation are disclosed. A first image having a first timestamp and a second image having a second timestamp are acquired. These images are generated by a camera, and the first timestamp is before the second timestamp. A motion compensation (MC) operation is performed on the first image to produce an MC image. A difference image is generated using the MC image and the second image. The difference image reflects differences in intensities that exist between the two images. A local weight map is generated based on those differences. A global weight map is generated based on certain IMU data. A final weight map is generated based on a combination of the local weight map and the global weight map. The final weight map is used to generate a filtered image.

Temporal filtering weight computation

A system for generating high dynamic range (HDR) imagery obtains a history frame associated with a first timepoint and with a first set of image capture parameters. The system obtains an image frame associated with a particular set of image capture parameters and captured at a second timepoint that is subsequent to the first timepoint, and the particular set of image capture parameters comprises the first set of image capture parameters or a second set of image capture parameters. The system generates a normalized image frame by applying a normalization operation to the image frame. The normalization operation may be determined based upon the particular set of image capture parameters. The system generates a weight map based upon at least the normalized image frame and generate an HDR image frame based upon the normalized image frame, the history frame, and the weight map.

High dynamic range image acquisition using temporal filtering

Systems are configured for generating temporally corrected pass-through images. In some instances, the systems obtain depth maps of an environment at a first timepoint, generate a 3D representation of the environment by unprojecting the depth information represented in the depth map, and obtain one or more first images of the environment captured at a second timepoint. The systems may also be configured to perform a first intermediate projection to identify first texture information from the one or more first images, identify a display pose associated with the system, generate a display projection of the 3D representation, and creating a composite image based on the display projection and the first texture information.

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Redmond, WA, United States of America

Christian Markus Maekelae