Speckle reduction in digital holography with Non-local means filter based on the structural similarity

Abstract Speckle noise limits the application of digital holography across various fields. This paper proposes a Non-local means filter method to suppress speckle noise by determining the weight of each traversed pixel based on the structural similarity between image blocks centered on the target and traversed pixels. Experimental results show that, compared to other typical digital image processing methods, this method can significantly reduce the speckle noise and exhibits a clear advantage across various metrics. These results indicate that the proposed method holds significant development potential in the field of speckle noise reduction.

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Publication Details

Journal
Physica Scripta
Published
2024-08-19
DOI
https://doi.org/10.1088/1402-4896/ad70f4
Primary Topic
Digital Holography and Microscopy
Type
article
Field-Weighted Citation Impact
0.00

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article

Speckle reduction in digital holography with Non-local means filter based on the structural similarity

Honghui Chen, Zhaoqian Xie, Li Chen, Kunhua Wen
Physica Scripta
Digital Holography and Microscopy
article

Speckle reduction in digital holography with Non-local means filter based on the structural similarity

Honghui Chen, Zhaoqian Xie, Li Chen, Kunhua Wen
article en

Abstract

Abstract Speckle noise limits the application of digital holography across various fields. This paper proposes a Non-local means filter method to suppress speckle noise by determining the weight of each traversed pixel based on the structural similarity between image blocks centered on the target and traversed pixels. Experimental results show that, compared to other typical digital image processing methods, this method can significantly reduce the speckle noise and exhibits a clear advantage across various metrics. These results indicate that the proposed method holds significant development potential in the field of speckle noise reduction.

Physica ScriptaVol. 99(10)
Guangdong University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 89%
Digital Holography and Microscopy
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