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Research Article Open access CC BY 4.0

Non-uniformity Correction Algorithm Based on Polynomial Fit Estimation

Yang Weiping, Zhang Yan, Zhang Zhilong

Current Journal of Applied Science and Technology · pp. 1–9 · Published 9 Sep 2015

10.9734/BJAST/2015/18926

Abstract

Because of many advantages such as all-weather work, passive imaging, high sensitivity, high frame frequency and simple structure, etc., IRFPA (infrared focal plane array) sensors have become popular in civil and military applications. However, images obtained by IRFPA suffer from a common problem called FPN (fixed pattern noise), which severely degrades image quality and limits the infrared imaging applications, and they can hardly be used without non-uniformity correction (NUC) on IR image. Therefore, it is urged to perform the NUC processing. As we all know, the algorithms of non-uniformity correction can be classified into two main categories, the calibration-based algorithm and the scene-based algorithm. But each kind of algorithm has its disadvantages, in order to make up for the limitations, a novel non-uniformity correction algorithm based on polynomial fit estimation and a modified factor is proposed, which combines the advantages of the two algorithms. Experimental results demonstrate that the proposed NUC algorithm has a good NUC effect with a lower non-uniformity ratio.

Non-uniformity correction polynomial fit estimation wo-point correction temporal Kalman filter

References (7)

  1. 1 Nonuniformity correction of infrared image sequences using the constant-statistics constraint [DOI]
  2. 2 Scene-based nonuniformity correction algorithm based on interframe registration [DOI]
  3. 3 Recursive Algorithms for Bias and Gain Nonuniformity Correction in Infrared Videos [DOI]
  4. 4 Scene based non-uniformity correction in thermal images using Kalman filter [DOI]
  5. 5 An Improved Non-uniformity Correction Algorithm for IRFPA Based on Neural Network [DOI]
  6. 6 Kalman-filtering approach for nonuniformity correction in focal plane array sensors [DOI]
  7. 7 IEEE Transactions on Image Processing

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