Sensors, Vol. 19, Pages 4076: Super-Resolution Reconstruction of Cell Pseudo-Color Image Based on Raman Technology

Sensors, Vol. 19, Pages 4076: Super-Resolution Reconstruction of Cell Pseudo-Color Image Based on Raman Technology Sensors doi: 10.3390/s19194076 Authors: Yifan Yang Ming Zhu Yuqing Wang Hang Yang Yanfeng Wu Bei Li Raman spectroscopy visualization is a challenging task due to the interference of complex background noise and the number of selected measurement points. In this paper, a super-resolution image reconstruction algorithm for Raman spectroscopy is studied to convert raw Raman data into pseudo-color super-resolution imaging. Firstly, the Raman spectrum data of a single measurement point is measured multiple times to calculate the mean value to remove the random background noise, and innovatively introduce the Retinex algorithm and the median filtering algorithm which improve the signal-to-noise ratio. The novel method of using deep neural network performs a super-resolution reconstruction operation on the gray image. An adaptive guided filter that automatically adjusts the filter radius and penalty factor is proposed to highlight the contour of the cell, and the super-resolution reconstruction of the pseudo-color image of the Raman spectrum is realized. The average signal-to-noise ratio of the reconstructed pseudo-color image sub-band reaches 14.29 db, and the average value of information entropy reaches 4.30 db. The results show that the Raman-based cell pseudo-color image super-resolution reconstruction algorithm is an effective tool to effectively ...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research

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