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A De-noising Algorithm of Infrared Image Contrast Enhancement

  • Changjiang Zhang
  • Xiaodong Wang
  • Haoran Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)

Abstract

An infrared image contrast enhancement algorithm based on discrete stationary wavelet transform (DSWT) and non-linear operator is proposed. Having implemented DSWT to an infrared image, de-noising is done by the method proposed in the high frequency sub-bands which are in the better resolution levels, and enhancement is implemented by combining a de-noising method with a non-linear gain method in the high frequency sub-bands which are in the worse resolution levels. Experiment results show that the new algorithm can effectively reduce the correlative noise (1/f noise), additive gauss white noise (AGWN) and multiplicative noise (MN) in the infrared image while also enhancing the contrast of the infrared image. In visual quality, the algorithm is better than the traditional unshaped mask method (USM), histogram equalization method (HIS), GWP method and WYQ method.

Keywords

Additive Gauss White Noise Visual Quality Infrared Image Multiplicative Noise Correlate Noise 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Changjiang Zhang
    • 1
  • Xiaodong Wang
    • 1
  • Haoran Zhang
    • 1
  1. 1.College of Information Science and EngineeringZhejiang Normal UniversityJinhuaChina

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