Investigation of a Robust Blind Deconvolution Algorithm Using Extracted Structures in Light Microscopy Images of Salivary Glands: A Pilot Study - Kim, Kyuseok; Kim, Jae-Young; Kim, Ji-Youn (Electronics (Basel), 2024)
Although light microscopy (LM) images are widely used to observe various bodily tissues, including salivary glands, reaching a satisfactory spatial resolution in the final images remains a major challenge. The objective of this study was to model a robust blind deconvolution algorithm using the extracted structure and analyze its applicability to LM images. Given LM images of the salivary glands, the proposed robust blind deconvolution method performs non-blind deconvolution after estimating the structural map and kernel of each image. To demonstrate the usefulness of the proposed algorithm for LM images, the perceptual sharpness index (PSI), Blanchet’s sharpness index (BSI), and natural image quality evaluator (NIQE) were used as evaluation metrics. We demonstrated that when the proposed algorithm was applied to salivary gland LM images, the PSI and BSI were improved by 7.95% and 7.44%, respectively, compared with those of the conventional TV-based algorithm. When the proposed algorithm was applied to an LM image, we confirmed that the NIQE value was similar to that of a low-resolution image. In conclusion, the proposed robust blind deconvolution algorithm is highly applicable to salivary gland LM images, and we expect that further applications will become possible.