Improvement of Image Classification by Multiple Optical Scattering

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Abstract
Multiple optical scattering occurs when light propagates in a non-uniform medium. During the multiple scattering, images were distorted and the spatial information they carried became scrambled. However, the image information is not lost but presents in the form of speckle patterns (SPs). In this study, we built up an optical random scattering system based on an LCD and an RGB laser source. We found that the image classification can be improved by the help of random scattering which is considered as a feedforward neural network to extracts features from image. Along with the ridge classification deployed on computer, we achieved excellent classification accuracy higher than 94%, for a variety of data sets covering medical, agricultural, environmental protection and other fields. In addition, the proposed optical scattering system has the advantages of high speed, low power consumption, and miniaturization, which is suitable for deploying in edge computing applications.
Funding Information
  • National Key R&D Program of China (2019YFE0112000, 2020YFF0217803)
  • Zhejiang Provincial Xinmiao Talents Program (2021R409043)
  • National Natural Science Foundation of China (11874332, 61727816, 61775202)
  • Key R&D plan of Zhejiang Province (2021C01179)
  • Zhejiang Provincial Natural Science Foundation of China (LY21F050006)
  • Science and Technology Program Project
  • State Administration for Market Regulation (2019MK147)

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