A new image fusion algorithm of dynamic contour based on IR and visible sensors

Abstract

IR and visible sensors are commonly used in tracking and recognition system of targets. Image fusion for these sensors can effectively improve system's accuracy of tracking and detection. But sampling rates of these sensors are usually different so that a new feature level image fusion scheme is devised in this paper. This scheme is universal and can be widely used in the detection and tracking of moving target when sampling rates of these sensors are largely different (i.e. radar and visible image). This fusion scheme is divided into two parts which are asynchronous and synchronous fusion. Target's contour is represented by dynamic contour. In asynchronous fusion, for the sensor with high sampling rate a multiple sequence image fusion method is devised based on statistical filtering model to get measurement estimation of target's contour. Then in synchronous fusion a real-time differential coupling is implemented for the estimation from asynchronous fusion and the image from the sensor with low sampling rate in order to effectively restrict convergent shape of dynamic contour in visible image. Contrasting simulation experiment proves our fusion scheme's efficacy and average tracking error in visible image with fusion has decreased by 68.31%.