A Study of Noise Reduction Algorithm Using Statistical Optimization in Digital Holographic Microscopy

Jongpil Jeong, Hyun-Woo Kim, Myungjin Cho, Min-Chul Lee

Abstract: Recently, due to the coronavirus era, we have a heightened need for fast and accurate diagnostics. To meet these requirements, there are many methods such as polymerase chain reaction, but they also require about from a few hours to a day. In contrast, a three-dimensional model of cells can be observed by simply extracting cells and photographing them with digital holographic microscopy, and in the case of diseases that can be classified b y t he shape of cells, diagnosis i s possible in a few minutes. However, there are precise focal issues and noise in the high-frequency domain, respectively. Therefore, to resolve these issues, we propose an optimization method by modifying the threshold value of the high variance pixel averaging method in digital holographic microscopy.

External IDs:dblp:conf/jcsse/JeongKCL24