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Single-Frame Infrared Image Non-Uniformity Correction Based on Wavelet Domain Noise Separation.
Mingqing Li1,2, Yuqing Wang1, Haijiang Sun1
1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.
Sensors (Basel, Switzerland)
|October 28, 2023
Summary
This study introduces a new method for infrared image non-uniformity correction (NUC) using wavelet domain noise separation. It effectively removes both high and low-frequency noise, improving image quality for demanding applications.
Area of Science:
- Infrared imaging
- Image processing
- Signal processing
Background:
- Current non-uniformity correction (NUC) methods for infrared imaging often overlook low-frequency noise and suffer from ghosting artifacts.
- Existing techniques primarily focus on high-frequency stripe noise, compromising overall image quality.
Purpose of the Study:
- To propose a novel single-frame infrared image non-uniformity correction method.
- To address limitations of existing NUC techniques by incorporating low-frequency noise correction and reducing ghosting.
Main Methods:
- Image decomposition into frequency components using wavelet transformation.
- Clustering algorithm for high-frequency noise extraction from vertical wavelet components.
- Surface fitting for low-frequency noise capture from approximate wavelet components.
- Noise component subtraction for image restoration.
Main Results:
- The proposed method achieved optimal Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index Measure (SSIM) on simulated images.
- Real-world infrared image sequences showed an average non-uniformity index reduction of 75.54%.
- The method demonstrates efficient processing with low computational overhead.
Conclusions:
- The wavelet domain noise separation method effectively corrects non-uniformity in single infrared frames.
- This technique significantly enhances image quality by addressing both high and low-frequency noise.
- The method is suitable for real-time infrared imaging applications with strict quality and speed requirements.
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