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Real-time infrared image detail enhancement based on fast guided image filter and plateau equalization

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Abstract

Image detail enhancement is critical to the performance of infrared imaging systems because the original images generally suffer from low contrast and a low signal-to-noise ratio. Although conventional decomposition-based methods have advantages in enhancing image details, they also have clear disadvantages, which include intensive computations, over-enhanced noise, and gradient reversal artifacts. In this paper, we propose to accelerate enhancement processing by using a fast guided filter and plateau equalization. Our method consists of image decomposition, base and detail layers processing, and projection of the enhanced image to an 8-bit dynamic range. Experimental results demonstrated that our proposed method achieves a good balance among detail enhancement performance, noise and gradient reversal artifacts suppression, and computational cost, with a frame rate around 30 fps for ${{640}} \times {{512}}$ infrared images.

© 2020 Optical Society of America

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