Objective evaluation method for MRTD of IR thermal imager

Dong Wei Wang*, Xu Sheng Zhang, Chuan He, Jia Ming Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Minimum Resolvable Temperature Difference (MRTD) is an important technical parameter to estimate the infrared thermal imager. The traditional measurement method based on the testers' subjective judging has poor reproducibility. To solve this problem, an objective evaluation method based on Artificial Neural Network (ANN) was developed. Two image features were put forward in the paper. Instead of human eyes, large numbers of image data were acquired by digital CCD and transferred to ANN. Then the ANN was trained by BP-Neural-Networks-based LM algorithm. The judging ability of well trained ANN was similar to the visual system of human eyes. The feasibility of the proposed method was proved through Matlab model and the developed software. And the test results show good accuracy and repeatability of the proposed method. It agrees well with the subjective one under the same test environment. The software system and equipment based on the proposed method had been successfully used in some test cases and greatly improved the test efficiency and accuracy.

Original languageEnglish
Pages (from-to)611-613+654
JournalHongwai yu Jiguang Gongcheng/Infrared and Laser Engineering
Volume39
Issue number4
Publication statusPublished - Aug 2010

Keywords

  • Artificial neural network
  • Infrared measurement
  • Infrared thermal imaging system
  • Objective evaluation for MRTD

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