CAMFv2: Better, faster and stronger for electrochemiluminescence image denoising

Electrochemiluminescence (ECL) is a phenomenon in which light is emitted when an electrochemical reaction occurs in a solution. ECL images are widely used in various fields. However, ECL images often carry considerable unavoidable noise. Prior to using ECL images, denoising it is very important. At present, the simplest and most valuable image denoising method is the center adaptive median filter (CAMF). However, in some images, CAMF does not work very well. There are three main kinds of images: images with excessive noise areas in the light spot, images with large differences in the size of the light spot, and images with different shapes of light spots. To make the CAMF problems easier to solve, we narrow the decision criteria for the current pixels inside and outside the spot, the selection of the filter size threshold, the selection of the nearest spot, the determination of the spot center, etc., and we then propose CAMFv2. Our experiments show that our CAMFv2 is better than CAMF.

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Publication Details

Journal
Applied Intelligence
Published
2025-06-19
DOI
https://doi.org/10.1007/s10489-025-06652-6
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

CAMFv2: Better, faster and stronger for electrochemiluminescence image denoising

Jun Li, Guan-Yu Chen, Jun Yang, Bing Yang et al.
Applied Intelligence
Advanced biosensing and bioanalysis techniques
article

CAMFv2: Better, faster and stronger for electrochemiluminescence image denoising

Jun Li, Guan-Yu Chen, Jun Yang, Bing Yang, Xinhang Jiang
article en

Abstract

Electrochemiluminescence (ECL) is a phenomenon in which light is emitted when an electrochemical reaction occurs in a solution. ECL images are widely used in various fields. However, ECL images often carry considerable unavoidable noise. Prior to using ECL images, denoising it is very important. At present, the simplest and most valuable image denoising method is the center adaptive median filter (CAMF). However, in some images, CAMF does not work very well. There are three main kinds of images: images with excessive noise areas in the light spot, images with large differences in the size of the light spot, and images with different shapes of light spots. To make the CAMF problems easier to solve, we narrow the decision criteria for the current pixels inside and outside the spot, the selection of the filter size threshold, the selection of the nearest spot, the determination of the spot center, etc., and we then propose CAMFv2. Our experiments show that our CAMFv2 is better than CAMF.

Applied IntelligenceVol. 55(11)
Sichuan Agricultural University (CN), Ya'an Polytechnic College (CN)
Natural Science Foundation of Sichuan Province
Openalex Percentile: Top 87%
Advanced biosensing and bioanalysis techniques
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CAMFv2: Better, faster and stronger for electrochemiluminescence image denoising — Jun Li, Guan-Yu Chen, et al. · Applied Intelligence (2025) | TGRS Research Map | TGRS