Conditional normalizing flow for variational single image super-resolution on microscopy images

Joel Ang; Alexander Yong; Chiyo Tan; Jessica Kng; Ko Hui Tan; Liyun Saw; Kaicheng Liang

doi:10.1117/12.2650254

17 March 2023 Conditional normalizing flow for variational single image super-resolution on microscopy images

Joel Ang, Alexander Yong, Chiyo Tan, Jessica Kng, Ko Hui Tan, Liyun Saw, Kaicheng Liang

Proceedings Volume PC12438, AI and Optical Data Sciences IV; PC124380V (2023) https://doi.org/10.1117/12.2650254
Event: SPIE OPTO, 2023, San Francisco, California, United States

Abstract

High-resolution images are necessary for various biological, clinical, and pathological applications. However, using objective lenses with high magnifications comes with its limitations: a smaller field of view, shorter working distance, limited depth of field, more intense illumination required, and a more complex illumination setup required. Single image super-resolution (SISR) could allow us to generate high-resolution images while still reaping the benefits of using low-magnification objectives. We developed SRFlow++, a conditional normalizing flow for SISR to empower our microscope with the ability to produce high-resolution (10x magnified) images of high fidelity and quality while using a low-magnification (4x) objective.

Conference Presentation

Citation Download Citation

Joel Ang, Alexander Yong, Chiyo Tan, Jessica Kng, Ko Hui Tan, Liyun Saw, and Kaicheng Liang "Conditional normalizing flow for variational single image super-resolution on microscopy images", Proc. SPIE PC12438, AI and Optical Data Sciences IV, PC124380V (17 March 2023); https://doi.org/10.1117/12.2650254

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