Speckle noise reduction for digital holographic images using multi-scale convolutional neural networks

Wonseok Jeon, Wooyoung Jeong, Kyungchan Son, Hyunseok Yang

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

In this Letter, we propose a fast speckle noise reduction method with only a single reconstructed image based on convolutional neural networks. The proposed network has multi-sized kernels that can capture the speckle noise component effectively from digital holographic images. For robust noise reduction performance, the network is trained with a large noisy image dataset that has object-dependent noise and a wide range of noise levels. The experimental results show the fast, robust, and outstanding speckle noise reduction performance of the proposed approach.

Original languageEnglish
Pages (from-to)4240-4243
Number of pages4
JournalOptics Letters
Volume43
Issue number17
DOIs
Publication statusPublished - 2018 Sep 1

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics

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