Research On SNR Characteristics And Decoding Algorithms Of Wavefront Coding System

The Wavefront Coding System encodes the incident light wave field by addingthe rotationally unsymmetrical phase mask at the plane of the pupil of the normal optical system. This method could makes the PSF or OTF of the optical system be insensitive to the aberration of defocus and expands the depth of the focus of the opticalsystem. Our method contains two steps: firstly, the method is proposed to generatea series of middle blurred encoded images with small difference in a certain opticalplanes of wave fields around the plane of the focus of the lens and then the image could be decoded perfectly through digital filtering. The paper is proposed trying to solve the problems caused by the amplification of the noise during the process of retrieving the original image and analyzed the imaging of the Wavefront Coding System,finally presenting the algorithm to solve the problem discussed above.The paper is proposed in three sections: First, we analyzed the character of invariance of defocus of the Wavefront Coding System based on the analyzing of the PSF and MTF followed by studying on the theories of encoding and decoding of theoptical system. Then we found that the retrieved images are seriously affected by the amplification of the noises added to the optical system in the process of encoding the images which contributed to the studying on the retrieval of the image in the Wavefront Coding System. Then we analyzed the noise in the optical system and built the mathematical models used for the noise and the Signal Noise Ratio (SNR) after which the amplification of the noise is calculated in the process of retrieving the images and the SNR of the middle images. Furthermore, the final images are discussed based on the character of imaging in the optical system. Finally, we represented a modified retrieval algorithm based on Wavelet transform and LR filtering method to retrieve the images with different kind of noises added to the images. In this section, we also discussed the effects of different algorithms used for reducing the noises. Then digital simulation is represented and the simulation results are shown in this section. The results are shown that the images are retrieved better with the algorithm we proposed compare to other algorithms.