A Neural Network Processing Method Based on Self-Assembly Equipment for Optical Image Display Standardization

Optical image is a kind of important data for communication because it is a two or three -dimensions data set to express communication information such as geographical signal, medical signal, remote sensing signal, etc. Thus, how to express the optical image properly is critical for the communication analytics. A new display method for optical image is described which is derived from the concept-Grayscale Standard Display Function (GSDF) which has been defined in DICOM, a medical image standard. The method analysis GSDF based on neural network processing which is different to DICOM. And the training data are from a self-assembly Equipment in NIM which is a traceable optical display equipment. Thus, the method has common usage for all optical image display, exceeding medical image. Furthermore, it is suitable for standardization because of the traceability.

Abstract licence: CC BY-NC-ND

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