Design and Implementation of a Real-Time Autofocus Algorithm for Thermal Imagers

Good image quality is the most important requirement of a thermal imager or any other imaging system in almost all applications. Degree of focus in an image plays a very important role in determining the image quality, thus focusing mechanism is a very important requirement in thermal imagers. A real-time and reliable passive autofocus algorithm has been developed and implemented in FPGA-based hardware. This autofocus module has been integrated with the video processing pipeline of thermal imagers. Prior to the hardware implementation, different algorithms for image sharpness evaluation have been implemented in MATLAB and simulations have been done with test video sequences acquired by a thermal imager with motorized focus control to analyze the algorithms efficiency. Cumulative gradient algorithm has been developed for image sharpness evaluation. The algorithm has been tested on images taken from a thermal imager under varying contrast and background conditions, and it shows high precision and good discriminating power. The images have been prefiltered by a median rank-order filter using a 3 × 3 matrix to make it more robust in handling noisy images. Complete autofocus algorithm design comprising of a frame acquisition module for acquiring user selectable central region in the incoming thermal imager video, Cumulative Gradient-based image sharpness evaluation module, fixed step size search-based focal plane search module and a motor pulse generation module for generating motor drives have been implemented on Xilinx FPGA device XC4VLX100 using Xilinx ISE EDA tool.