It is determined by the switching rule to switch the subsystem, and only one subsystem can work at each moment. On the other hand, the switching system is the concept of control engineering field and вЂњswitchingвЂќ was first introduced into the control system by the switching servo system. In addition, based on the joint filtering algorithm of the image processing system, the processed filtering image is accurate and smooth, but it also violates the real-time requirements of the system. The filtering method with impulse noise filter is relatively accurate, but the algorithm is more complicated, the steps are numerous, and the calculation takes a long time, which is not conducive to the real-time performance of the interactive projection system, and the accuracy requirements of the actual system for the filtered image are not so strict. Therefore, the maximum interference at the current time should be analyzed first and then the filtering algorithm should be selected corresponding to the main interference source.ДЄlthough the image denoising hybrid filtering method can effectively improve the signal-to-noise ratio improvement factor, it does not consider the image processing time, which is not chosen in practical systems. If the same image has a variety of hybrid filtering, it will affect the system real-time performance. These noises often appear at the same time. Among these noises, Gaussian noise and the salt-and-pepper noise are the two most important types of noise. In addition, the short stay at the time of image formation and the interference of the channel during image transmission are also the main reasons for the noise generation.

In the case of the filter system based on Kinect sensor depth image, light intensity and sensor temperature are the main factors that generate the noise in the image. In practice, a variety of noise generation methods have demonstrated that a single filtering algorithm cannot be effective for all types of image filtering. All of these algorithms have their own advantages and disadvantages and are proposed for specific noise. Meanwhile, the nonlinear filtering methods include median filtering, bilateral filtering, and their improved algorithms. The commonly used linear filtering methods include mean filtering, Gaussian filtering, and their improved algorithms. From the view of design method, the filtering algorithm can be divided into two categories: linear filtering and nonlinear filtering. The currently available digital image filtering methods are also applicable to deep images. Therefore, it is essential to smooth the image in the preprocessing. These noises reduce the image accuracy, which affects the subsequent work such as image segmentation, tracking, feature extraction, and recognition, and also cause serious disturbance to target recognition and tracking. Large-screen interactive projection systems based on depth images are inevitably polluted by a variety of mixed noise due to various factors. The experimental results demonstrate and validate that the proposed switching filter algorithm not only effectively removes the noise but also ensures the real-time performance of tracking and achieves good target tracking performance, which makes it applicable in various image filtering processing systems. In this paper, the switching system method is introduced into the filter for the first time, and an arbitrary switching filter algorithm is proposed and applied to the depth image filtering system based on Kinect sensor. Although the hybrid filter can guarantee the accuracy of the image, but the algorithm is complex and time-consuming, which affects the real-time performance of the interactive projection system. Generally, several filtering methods are used in combination to resolve this problem. The interactive projection systems based on deep images are usually disturbed by the mixed noise.

Gaussian filter matlab 2009