Reconfigurable hybrid vision enhancement system using tone mapping and adaptive gamma correction algorithm for night surveillance robot

Night vision system has become a critical component of modern warfare and the ability to see in nighttime conditions allows military maneuvers and a potential advantage to the forces equipped with this technology. These night vision systems rely on the very low light levels of night sky illumination to help image the targeted scene and its surroundings. Many research works have been undertaken to overcome issues in hardware implementation. In this paper, we contribute to enhance night vision sources by hybrid vision enhancement (HVE) system without affecting performance of hardware implementation. The proposed hybrid system consists of two algorithms such asoptimizedtone mapping (OTM) and adaptive gamma correction (AGC) algorithm. Normally, hybrid systems are not an area efficient, here we modify the tone mapping algorithm byoptimized filter design with the exponential basis. The differential evolution optimization algorithm is used to enhance the filter design. The proposed HVE system implementation is designed in Verilog language and synthesized with different FPGA device families in Xilinx tool. Simulation result shows that our proposed HVE system is able to enhance vision of wide dynamic range (WDR) images to good visual quality. The synthesis result shows that our proposed HVE system perform very efficient than existing system in terms of hardware utilization, maximum clock frequency, and power.