Developed and integrated a CUDA-accelerated exposure correction filter for the Chrono::Sensor image processing pipeline in the uwsbel/chrono-wisc repository. This feature dynamically adjusts image brightness based on exposure time, enhancing the reliability of sensor data under varying lighting conditions. The implementation leveraged C++ and CUDA to ensure efficient processing and seamless integration within the existing sensor framework. Updated SWIG bindings exposed the new filter to both sensor and robot components, broadening its applicability across the system. The work focused on improving image quality and consistency, supporting more robust downstream perception and analytics without introducing new bugs during the development period.