Image De-Noising Method Using Photoelectric Sensor Based on Wavelet Transform and Shearlet Transform

In the process of image acquisition, coding and reconstruction, noise caused by equipment, light, etc., often occurs. Therefore, an important goal of image processing is to eliminate noise as much as possible. In this study, a wireless network topology based on the PAN3101 photoelectric sensor is constructed, and CC2530 is used as the main control chip. The design of the node system is simulated, the device is selected and the circuit design is combined with the photoelectric sensor. The principles of the conventional wavelet transform and the Shearlet transform are studied. An integrated denoising algorithm with the combination of wavelet and improved Shearlet transform is used. The denoising algorithm is applied to the post-processing of the wireless sensor network (WSN) community video images. Using the power control algorithm of the adjacent graph, the number of nodes and the transmission distance involved in the WSN model are determined, and the experimental and error accuracy are satisfied. Under the premise of designing the node system and hardware structure, the image of a relatively high quality is obtained. In the image post-processing experiment based on the proposed denoising algorithm, a large number of experiments show that the algorithm enables the image to have a better visual effect and the edge of the image is sharper. Thus shows excellent denoising performance and providing a clearer image for the unmanned video detection in the community.