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Infrared Stripe Correction Algorithm Based on Wavelet Analysis and Gradient Equalization

1,2,*, 1,2,3, 1,2, 1,2 and 1,2
1
Shenyang Institute of Automation, Chinese Academy of Sciences, 114, Nanta Street, Shenhe District, Shenyang 110016, Liaoning, China
2
Key Laboratory of Optical Electrical Image Processing, Chinese Academy of Sciences, 114, Nanta Street, Shenhe District, Shenyang 110016, Liaoning, China
3
College of automation and electrical engineering, Shenyang University of Technology, NO. 6, Nanping Middle Road, Hunnan District, Shenyang 110159, Liaoning, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(10), 1993; https://doi.org/10.3390/app9101993
Received: 5 April 2019 / Revised: 10 May 2019 / Accepted: 10 May 2019 / Published: 15 May 2019
(This article belongs to the Special Issue Advanced Intelligent Imaging Technology)
PDF [5011 KB, uploaded 15 May 2019]
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Abstract

In the uncooled infrared imaging systems, owing to the non-uniformity of the amplifier in the readout circuit, the infrared image has obvious stripe noise, which greatly affects its quality. In this study, the generation mechanism of stripe noise is analyzed, and a new stripe correction algorithm based on wavelet analysis and gradient equalization is proposed, according to the single-direction distribution of the fixed image noise of infrared focal plane array. The raw infrared image is transformed by a wavelet transform, and the cumulative histogram of the vertical component is convolved by a Gaussian operator with a one-dimensional matrix, in order to achieve gradient equalization in the horizontal direction. In addition, the stripe noise is further separated from the edge texture by a guided filter. The algorithm is verified by simulating noised image and real infrared image, and the comparison experiment and qualitative and quantitative analysis with the current advanced algorithm show that the correction result of the algorithm in this paper is not only mild in visual effect, but also that the structural similarity (SSIM) and peak signal-to-noise ratio (PSNR) indexes can get the best result. It is shown that this algorithm can effectively remove stripe noise without losing details, and the correction performance of this method is better than the most advanced method.
Keywords: non-uniformity correction; focal-plane array; infrared image; destriping non-uniformity correction; focal-plane array; infrared image; destriping
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Wang, E.; Jiang, P.; Hou, X.; Zhu, Y.; Peng, L. Infrared Stripe Correction Algorithm Based on Wavelet Analysis and Gradient Equalization. Appl. Sci. 2019, 9, 1993.

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