The endoscopic defogging algorithm has a wide range of applications in the medical field, providing clear and real-time images for clinical doctors. Although significant progress has been made in defogging technology, the complexity of defogging algorithms is relatively high, making hardware implementation difficult in complex situations such as endoscopes. In order to achieve real-time defogging of endoscopes on hardware, improvements were made to the dark channel prior algorithm to reduce hardware resource consumption and time complexity. The improved algorithm selects suitable atmospheric light intensity estimation values, transmittance compensation values for hardware, and uses a pipeline structure to achieve the processing of foggy images. The hardware circuit of the algorithm is implemented using Xilinx's ZYNQ7020, with a real-time processing resolution of 640×480 video images, with a speed of up to 260f/s, consume only 1.28K LUT, and consume 619 registers. The experimental results show that compared to traditional algorithms, the improved algorithm has the characteristics of fast processing speed, low power consumption, and strong portability, meeting the requirements of real-time video processing for endoscopes.

[2023-12-18] Accepted Paper /doc/2023.09.0436/v1