Abstract
This paper proposes a new algorithm based on energy features for noise reduction using wavelets. The device noise profile is obtained by the noise images taken from the imaging device so that it can represent the device’s noise in multi-scale and multi-band. The energy feature takes advantage of the inter-scale relationship and spatial relationship of wavelet transformation. The wavelet coefficients are shrunk by the likelihood of noise or signal based on its energy level. The de-noised images are obtained by wavelet reconstruction. The results and comparison against common used methods show that the performance of our method is very promising despite simple structure.
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© 2008 Springer-Verlag Berlin Heidelberg
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Fu, G., Hojjat, A., Colchester, A. (2008). Wavelet Noise Reduction Based on Energy Features. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_8
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DOI: https://doi.org/10.1007/978-3-540-69812-8_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69811-1
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