Abstract
Aiming at the problem of low contrast and unclear edge of gray image in hyperspectral transmission imaging, the single-channel grayscale processing algorithm was applied to the simulated image based on the simulation experiment. The experiment shows that this algorithm improves the contrast to a certain extent and enhances the image edge and grayscale image quality. While improving the quality of grayscale images, this algorithm also triples the number of original images, providing a data enhancement method for heterogeneity detection using deep learning. Therefore, this experiment verifies the feasibility of the single-channel processing algorithm and may provide a method for multispectral transmission biological tissue images, it may be a data enhancement method that can be applied to deep learning for tissue image detection.
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Acknowledgements
The authors would love to acknowledge funding from NYSFC and TSF. This work was partially supported by the Natural Youth Science Foundation of China (NYSFC-61401310) and the Tianjin Science Foundation (TSF-18JCYBJC86400).
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Zhang, B., Zhang, C., Li, G., Lin, L., Zhang, C., Wang, F. (2020). Single-Channel Grayscale Processing Algorithm for Transmission Tissue Images Based on Heterogeneity Detection. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_61
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DOI: https://doi.org/10.1007/978-981-13-9409-6_61
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