Nonuniformity correction for internal radiation in uncooled infrared imaging based on gradient-weighted guided image...

Area of Science:

• Infrared Imaging Technology
• Image Processing Algorithms
• Optical System Calibration

Background:

• Uncooled infrared focal plane array imaging performance degrades due to internal radiation.
• Existing nonuniformity correction methods fail to adequately address fixed-pattern noise from internal radiation.

Purpose of the Study:

• To introduce and evaluate the GWGF-IR algorithm for correcting internal radiation-induced fixed-pattern noise.
• To enhance the performance and reliability of uncooled infrared imaging systems.

Main Methods:

• Developed a gradient-weighted guided image filter (GWGF-IR) to extract internal radiation noise gradients.
• Implemented a self-adaptive estimation method for gradient weight factors and regularization parameters.
• Utilized a weighted quadratic cost function with gradient weight factors for noise correction.

Main Results:

• GWGF-IR adaptively corrects internal radiation noise across various image intensities and scenes.
• Achieved significant improvements in subjective visual effects and objective metrics (PSNR, MMSIM).
• Demonstrated a 45.7% reduction in processing time compared to suboptimal algorithms.

Conclusions:

• GWGF-IR offers superior performance in correcting internal radiation noise for uncooled infrared imaging.
• The self-adaptive approach enhances the algorithm's applicability to diverse imaging conditions.
• GWGF-IR represents a significant advancement in infrared image nonuniformity correction.