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Abstract

In an endoscope system, a processor is programmed to control the image sensor and/or illumination to underexpose or overexpose every other frame of the video image data. The image sensor generates image data at a frame rate. Successive pairs of frames of the image data are combined to recover dynamic range and detail in over-bright or over-dark portions of the image, and the combined frames have the full frame rate of the video as generated by the image sensor. A machine learning model processes the video to simultaneously upsample the image data to a resolution higher than that captured by the image sensor, to sharpen edges, and to enhance local contrast. A two-output PID control algorithm controls exposure intensity by controlling at least two of gain, exposure, and illumination to achieve image display at a setpoint intensity, maximum change per step of the PID control damped to prevent oscillation.

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First Claim