Image Processing Based On Spatial Light Modulator

Optical wavelet transform is the combination of optical information processing and wavelet theory. It integrates many advantages of optical science and wavelet transform such as parallelism, high-speed and large capacity. It provides advantageous basis for the high-speed information processing. By now, it has got achievements on pattern recognition and texture segmentation. But the reports in optical image data compression are rare because it has special requirements on the precision of the whole optical system.Basic principles and developments about optical information processing were introduced in the papers, then the photoelectric coupling device---spatial light modulator was studied deeply while corresponding concepts, structural characteristics and working principles were expatiated, after that its applications in optical image processing system were discussed. As optical filter was an important device of optical wavelet system, investigations and researches on several optical filters were carried out including spatial light modulator, film, CGH and grating. With the special requirements and performance comparison in consideration, SLM was ultimately selected as the optical filter in our system.In optical system the requirements and positioning precision on optical filter were key factors. According to the existing experiment conditions requirements on quantization and size of the optical filter were analyzed and calculated. Simulations were done to analyze the effect of filter size on image processing. At last the size of optical filter was finalized. Combining with the existing system, methods of measuring filter angle and positioning spectral filter were proposed. Experiments were done in the optimized system and the results were quite good.As the coherent light was used to illuminate there were lots of coherent noise in the image acquired on the output plane. From the point of reducing coherent noise and combining with the multiple spectrum caused by SLM a denoising method based on spatial average was proposed. The results proved that the method was effective in reducing some part of noise and retaining image details.