TEXTURE-PRESERVING HALO SUPPRESSION FOR IMAGING SYSTEMS

    公开(公告)号:US20250037250A1

    公开(公告)日:2025-01-30

    申请号:US18490505

    申请日:2023-10-19

    Abstract: A method includes obtaining, using at least one processing device of an electronic device, an input image containing blur. The method also includes generating, using the at least one processing device, an edge enhancement mask and a gain mask based on the input image. The method further includes generating, using the at least one processing device, a halo-suppressed edge mask based on the edge enhancement mask and the gain mask. In addition, the method includes generating, using the at least one processing device, a sharpened image based on the input image and the halo-suppressed edge mask.

    System and method for motion warping using multi-exposure frames

    公开(公告)号:US12206993B2

    公开(公告)日:2025-01-21

    申请号:US17938013

    申请日:2022-10-04

    Abstract: A method includes obtaining, using at least one image sensor of an electronic device, a first image frame and multiple second image frames of a scene. Each of the second image frames has an exposure time different from an exposure time of the first image frame. The method also includes generating, using at least one processor, blur kernels indicating a motion direction of the first image frame using an optical flow network. The method further includes refining, using the at least one processor, the blur kernels using a convolutional neural network. In addition, the method includes generating, using the at least one processor, a target image frame of the scene using the refined blur kernels and occlusion masks for the second image frames.

    Global tone mapping with contrast enhancement and chroma boost

    公开(公告)号:US12086971B2

    公开(公告)日:2024-09-10

    申请号:US17586511

    申请日:2022-01-27

    CPC classification number: G06T5/92 G06T5/40 G06T2207/10024

    Abstract: An apparatus includes at least one processing device configured to obtain an input image and determine a cumulative distribution function (CDF) histogram from a luminance or luma (Y) channel of the input image. The at least one processing device is also configured to determine an entry CDF histogram in a CDF histogram lookup table (LUT) closest to the determined CDF histogram. The at least one processing device is further configured to apply a Y channel global tone mapping (GTM) curve to the input image based on one or more parameters assigned to the entry CDF histogram from the CDF histogram LUT.

    MACHINE LEARNING-BASED APPROACHES FOR SYNTHETIC TRAINING DATA GENERATION AND IMAGE SHARPENING

    公开(公告)号:US20240062342A1

    公开(公告)日:2024-02-22

    申请号:US17820795

    申请日:2022-08-18

    CPC classification number: G06T5/002 G06T2207/20081 G06T2207/20084

    Abstract: A method includes obtaining an input image that contains blur. The method also includes providing the input image to a trained machine learning model, where the trained machine learning model includes (i) a shallow feature extractor configured to extract one or more feature maps from the input image and (ii) a deep feature extractor configured to extract deep features from the one or more feature maps. The method further includes using the trained machine learning model to generate a sharpened output image. The trained machine learning model is trained using ground truth training images and input training images, where the input training images include versions of the ground truth training images with blur created using demosaic and noise filtering operations.

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