Abstract: Electronic devices, methods, and program storage devices for leveraging machine learning to perform high-resolution and low latency image fusion and/or noise reduction are disclosed. An incoming image stream may be obtained from an image capture device, wherein the incoming image stream comprises a variety of differently-exposed captures, e.g., EV0 images, EV? images, EV+ images, long exposure images, EV0/EV? image pairs, etc., which are received according to a particular pattern. When a capture request is received, two or more intermediate assets may be generated from images from the incoming image stream and fed into a neural network that has been trained to fuse and/or noise reduce the intermediate assets. In some embodiments, the resultant fused image generated from the two or more intermediate assets may have a higher resolution than at least one of the images that were used to generate at least one of the two or more intermediate assets.

Abstract: A solution to the problem of image and video stitching is disclosed that compensates for the effects of lens distortion, camera misalignment, and parallax in combining multiple images. The disclosed image stitching technique includes depth or disparity estimation, alignment, and blending processes configured to be computationally efficient and produce quality results by limiting the presence of noticeable seams and artifacts in the final stitched image. An inter-frame approach applies image stitching to video frames to maintain temporal continuity between successive frames across a stitched video output having a 360-degree viewing perspective. A temporal adjustment is configured to improve temporal continuity between a subsequent frame and a previous frame in a sequence of video frames.

Abstract: A solution to the problem of image and video stitching is disclosed that compensates for the effects of lens distortion, camera misalignment, and parallax in combining multiple images. The disclosed image stitching technique includes depth or disparity estimation, alignment, and blending processes configured to be computationally efficient and produce quality results by limiting the presence of noticeable seams and artifacts in the final stitched image. An inter-frame approach applies image stitching to video frames to maintain temporal continuity between successive frames across a stitched video output having a 360-degree viewing perspective. A temporal adjustment is configured to improve temporal continuity between a subsequent frame and a previous frame in a sequence of video frames.