Single-Channel Grayscale Processing Algorithm for Transmission Tissue Images Based on Heterogeneity Detection
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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.
KeywordsMultispectral tissue image processing Image graying Grayscale image quality Target detection
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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