Multiframe image processing using semantic saliency

    公开(公告)号:US10719927B2

    公开(公告)日:2020-07-21

    申请号:US15862492

    申请日:2018-01-04

    Abstract: An electronic device, method, and computer readable medium for multi-frame image processing using semantic saliency are provided. The electronic device includes a camera, a display, and a processor. The processor is coupled to the camera and the display. The processor receives a plurality of frames captured by the camera during a capture event; identifies a salient region in each of the plurality of frames; determines a reference frame from the plurality of frames based on the identified salient regions; fuses non-reference frames with the determined reference frame into a completed image output.

    Apparatus and method for interband denoising and sharpening of images

    公开(公告)号:US12254601B2

    公开(公告)日:2025-03-18

    申请号:US17586435

    申请日:2022-01-27

    Abstract: A method includes obtaining a blended red-green-blue (RGB) image frame of a scene. The method also includes performing, using at least one processing device of an electronic device, an interband denoising operation to remove at least one of noise and one or more artifacts from the blended RGB image frame in order to produce a denoised RGB image frame. Performing the interband denoising operation includes performing filtering of red, green, and blue color channels of the blended RGB image frame to remove at least one of the noise and the one or more artifacts from the blended RGB image frame. The filtering of the red and blue color channels of the blended RGB image frame is based on image data of at least one of the green color channel and a white color channel of the blended RGB image frame.

    MULTI-STAGE MULTI-FRAME DENOISING WITH NEURAL RADIANCE FIELD NETWORKS OR OTHER MACHINE LEARNING MODELS

    公开(公告)号:US20250022098A1

    公开(公告)日:2025-01-16

    申请号:US18350558

    申请日:2023-07-11

    Abstract: A method includes obtaining, using at least one processing device of an electronic device, raw image frames of a scene. The raw image frames include different sets of raw image frames captured at different viewpoints and different viewing angles relative to the scene. The method also includes performing, using the at least one processing device, blending of each set of raw image frames in order to generate blended image frames of the scene. The method further includes training, using the at least one processing device, a machine learning model using the blended image frames. The machine learning model is trained to generate three-dimensional (3D) information about the scene from viewpoints and viewing angles not captured in the sets of raw image frames.

    Apparatus and method for combined intraband and interband multi-frame demosaicing

    公开(公告)号:US12148124B2

    公开(公告)日:2024-11-19

    申请号:US17649095

    申请日:2022-01-27

    Abstract: A method includes obtaining multiple input image frames and determining how to warp at least one of the input image frames. The method also includes performing an intraband demosaic-warp operation to reconstruct image data in different color channels of the input image frames and warp the at least one input image frame to produce RGB input image frames. The method further includes blending the RGB input image frames to produce a blended RGB image frame, performing an interband denoising operation to produce a denoised RGB image frame, and performing an interband sharpening operation to produce a sharpened RGB image frame. In addition, the method includes performing an interband demosaic operation to substantially equalize high-frequency content in different color channels of the sharpened RGB image frame to produce an equalized sharpened RGB image frame and generating a final image of the scene based on the equalized sharpened RGB image frame.

    Multi-frame depth-based multi-camera relighting of images

    公开(公告)号:US12141894B2

    公开(公告)日:2024-11-12

    申请号:US17566320

    申请日:2021-12-30

    Abstract: A method includes capturing a plurality of first images using a first image sensor and capturing a plurality of second images using a second image sensor. The method also includes estimating depth information based on at least one of the first images and at least one of the second images. The method further includes obtaining information related to a lighting direction from an artificial intelligence (AI) light director, where the AI light director is trained to determine one or more lighting directions. In addition, the method includes generating at least one relit image using at least one of the first and second images based on the obtained information related to the lighting direction and the estimated depth information.

    Hand motion pattern modeling and motion blur synthesizing techniques

    公开(公告)号:US12079971B2

    公开(公告)日:2024-09-03

    申请号:US17666166

    申请日:2022-02-07

    Abstract: A method includes obtaining, using a stationary sensor of an electronic device, multiple image frames including first and second image frames. The method also includes generating, using multiple previously generated motion vectors, a first motion-distorted image frame using the first image frame and a second motion-distorted image frame using the second image frame. The method further includes adding noise to the motion-distorted image frames to generate first and second noisy motion-distorted image frames. The method also includes performing (i) a first multi-frame processing (MFP) operation to generate a ground truth image using the motion-distorted image frames and (ii) a second MFP operation to generate an input image using the noisy motion-distorted image frames. In addition, the method includes storing the ground truth and input images as an image pair for training an artificial intelligence/machine learning (AI/ML)-based image processing operation for removing image distortions caused by handheld image capture.

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