CLOSED-LOOP AUTOTUNING FRAMEWORK FOR IMAGE SIGNAL PROCESSOR TUNING

    公开(公告)号:US20240169509A1

    公开(公告)日:2024-05-23

    申请号:US18058593

    申请日:2022-11-23

    Abstract: The disclosure describes an autotuning framework for tuning an image signal processing (ISP) module of an autonomous driving vehicle (ADV). The autotuning framework can generate different sets of parameter values using a variety of optimization algorithms to configure the ISP module. Each processed image generated by the ISP module configured with the different sets of parameter values is compared by an ISP module testing device with a reference image stored therein to generate an objective core measuring one or more differences between each of the processed images and the reference image. The objective scores and the corresponding sets of parameter values are stored in a database. Different sets of optimal parameter values for different environments can be selected from the database, and uploaded to a cloud database for use by an ADV, which can select a different set of ISP parameter values based on an environment that the ADV is travelling in.

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