Separating Particulate Matter From a Single Microscopic Image
Tushar Sandhan, Jin Young Choi; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 4584-4593
Abstract
Particulate matter (PM) is the blend of various solid and liquid particles suspended in atmosphere. These submicron particles are imperceptible for usual hand-held camera photography, but become a great obstacle in microscopic imaging. PM removal from a single microscopic image is a highly ill-posed and one of the challenging image denoising problems. In this work, we thoroughly analyze the physical properties of PM, microscope and their inevitable interaction; and propose an optimization scheme, which removes the PM from a high-resolution microscopic image within a few seconds. Experiments on real world microscopic images show that the proposed method significantly outperforms other competitive image denoising methods. It preserves the comprehensive microscopic foreground details while clearly separating the PM from a single monochromatic or color image.
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bibtex]
@InProceedings{Sandhan_2020_CVPR,
author = {Sandhan, Tushar and Choi, Jin Young},
title = {Separating Particulate Matter From a Single Microscopic Image},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}