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Denoising Method for Passive Photon Counting Images Based on Block-Matching 3D Filter and Non-Subsampled Contourlet
Xuan Wang1, Liju Yin2, Mingliang Gao3
1School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, Shandong, China. 18753370762@163.com.
Sensors (Basel, Switzerland)
|June 1, 2019
Summary
This study presents a new method to improve low-light images from photon counting detectors. The technique enhances image quality by reducing noise and improving contrast, leading to clearer visual results.
Area of Science:
- Image Processing
- Photon Counting Technology
- Computer Vision
Background:
- Photon counting detectors generate low-light images with issues like poor contrast and brightness.
- Existing denoising and enhancement methods struggle with the unique noise characteristics of photon counting images.
Purpose of the Study:
- To develop an effective denoising and enhancement method for low-light images from photon counting detectors.
- To improve visual quality and preserve details in photon counting images.
Main Methods:
- Applied non-subsampled contourlet transform (NSCT) to decompose images into frequency sub-bands.
- Utilized adaptive Retinex enhancement for low-frequency components and Bayes-shrink thresholding for high-frequency components.
- Implemented an improved block-matching 3D filter for final denoising and reduced processing time.
Main Results:
- The proposed method significantly reduced noise and enhanced contrast and brightness in low-light images.
- Objective evaluation indices showed superior performance compared to existing methods.
- The enhanced images exhibited improved visual effects and preserved fine details.
Conclusions:
- The combined NSCT and block-matching 3D filter approach effectively addresses denoising and enhancement challenges in photon counting images.
- This method offers a superior solution for improving the visual quality of low-light imagery from photon counting detectors.
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