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Infrared image enhancement using H(infinity) bounds for surveillance applications
1Department of Computer Science and Engineering, Qatar University, Doha, Qatar. uqidwai@qu.edu.qa
Summary
This study introduces two novel algorithms to enhance infrared (IR) images for surveillance. These methods improve visual quality by mapping IR pixels to optical space, offering a solution for real-time applications.
Area of Science:
- Image Processing
- Computer Vision
- Signal Processing
Background:
- Infrared (IR) imaging is crucial for surveillance but often suffers from low visual quality.
- Existing H(infinity)-based algorithms for image enhancement are computationally complex and unsuitable for real-time applications.
Purpose of the Study:
- To develop and implement two novel algorithms for enhancing infrared (IR) images.
- To improve the visual quality of IR images for practical surveillance applications.
Main Methods:
- Utilized autoregressive moving average (ARMA) model structure.
- Applied H(infinity) optimal bounds for pixel mapping.
- Developed and implemented two variants of H(infinity) algorithms suitable for real-time use.
Main Results:
- Demonstrated significant enhancement in the visual quality of acquired IR images.
- Theoretical and algorithmic results confirm the effectiveness of the proposed methods.
- The algorithms successfully map IR pixel space to normal optical image space.
Conclusions:
- The developed algorithms effectively enhance IR images, improving visual quality for surveillance.
- The proposed methods offer a viable solution for real-time IR image enhancement.
- This research contributes to advancing IR imaging technology for security and monitoring.
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