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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Zhang, C., Wang, X., Zhang, H. (2006). A De-noising Algorithm of Infrared Image Contrast Enhancement. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_111
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DOI: https://doi.org/10.1007/11739685_111
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33584-9
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