Digital Image Processing and Analysis Based on Particle Filter

Abstract

Image processing is the basic part of image engineering, which mainly studies image transformation, image enhancement, image scaling and image segmentation and decomposition. With the rapid development of science and technology, images have become the main source and important means to obtain external information, which is intuitive, vivid and efficient. It is widely used in information transmission and communication. Particle filter theory is a combination of Bayesian filter theory and Monte Carlo simulation theory, which is applicable to any nonlinear system that can be represented by state space model and nonlinear system that cannot be represented by traditional Kalman filter, and its accuracy can approach the optimal estimation. In this paper, the particle filter algorithm is applied to the digital image processing of target tracking. When the tracking target is completely occluded, the extended Kalman filter is applied to predict the position and state of the target, so that the algorithm can accurately track the target when the tracking target is occluded, thus realizing the adaptability of the algorithm to occlusion.