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公开(公告)号:US20220060619A1
公开(公告)日:2022-02-24
申请号:US17158917
申请日:2021-01-26
Applicant: QUALCOMM Incorporated
Inventor: Eran PINHASOV , Scott CHENG , Eran SCHARAM , Anatoly GUREVICH
Abstract: Examples are described for applying different settings for image capture to different portions of image data. For example, an image sensor can capture image data of a scene and can send the image data to an image signal processor (ISP) and a classification engine for processing. The classification engine can determine that a first object image region depicts a first category of object, and a second object image region depicts a second category of object. Different confidence regions of the image data can identify different degrees of confidence in the classifications. The ISP can generate an image by applying a different settings to the different portions of the image data. The different portions of the image data can be identified based on the object image regions and confidence regions.
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公开(公告)号:US20240121521A1
公开(公告)日:2024-04-11
申请号:US18545799
申请日:2023-12-19
Applicant: QUALCOMM Incorporated
Inventor: Eran PINHASOV , Scott CHENG , Eran SCHARAM , Anatoly GUREVICH
CPC classification number: H04N23/80 , G06V10/10 , G06V20/10 , G06V20/35 , H04N1/6072 , H04N1/6083 , H04N23/61 , H04N23/66 , H04N23/70 , H04N2101/00
Abstract: Examples are described for applying different settings for image capture to different portions of image data. For example, an image sensor can capture image data of a scene and can send the image data to an image signal processor (ISP) and a classification engine for processing. The classification engine can determine that a first object image region depicts a first category of object, and a second object image region depicts a second category of object. Different confidence regions of the image data can identify different degrees of confidence in the classifications. The ISP can generate an image by applying a different settings to the different portions of the image data. The different portions of the image data can be identified based on the object image regions and confidence regions.
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