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Improving the Quality of Multi-spectral Transmission Image Based on Modulation-frame Accumulation and Local Linear Embedding Algorithm

In biological tissue, optical transmission imaging is blurred due to absorption and scattering effects, which makes it difficult to detect heterogeneities on multi-spectral transmission image. In this paper, the inter-combination of modulation-frame accumulation and local linear embedding (LLE) super-resolution (SR) image reconstruction algorithm is introduced into multi-spectral transmission images for the first time to improve the quality of image. Firstly, the acquisition experiment of signal modulated phantom multi-spectral transmission image is designed. Secondly, frame accumulation processing is performed on the obtained multi-spectral transmission image. Meanwhile, the four-wavelength images with the same concentration ratio are recombined every three wavelengths to obtain true-color images, and the fusion principle is carried out in sequence of blue, green, red and near-infrared light. Then, multi-spectral true-color images are processed by LLE-SR model. Finally, the improvement of image quality is verified by full reference image quality assessment (FR-IQA). The experimental results show that frame accumulation, original-LLE and frame accumulation-LLE models proposed in this paper can improve the quality of multi-spectral transmission images. Among them, the original-LLE model in the FR-IQA index shows that the use of local linear correlation to restore the high precision of multi-spectral transmission image is more effective. In conclusion, based on the inter-combination of the above different image processing methods, this paper achieves the acquisition of high-quality multi-spectral transmission images, which will further improve the possibility of the application of optical transmission imaging technology in clinical screening of breast tumors.