A New Adaptive Image Denoising Method Based on Wavelet Packet Transform and Neighbor Dependency

Abstract:

In image processing, removal of noise without blurring the image edges is a difficult problem. Aiming at orthogonal wavelet transform and traditional thresholds shortage, a new adaptive threshold image de-noising method which is based on wavelet packet transform and neighbor dependency is proposed. Low frequency part and high frequency part can be decomposed at the same time in wavelet packet transform and the information contained in wavelet coefficients is redundant. Using this kind of relativity in wavelet packet coefficients, we use a new variance neighbor estimation method and then neighbor dependency adaptive threshold is produced. From the experiment result, we see that compared with traditional methods, this method can not only effectively eliminate noise, but can also well keep original images information and the quality after image de-noising is very well.

• Periodical: Applied Mechanics and Materials (Volumes 433-435)
• Pages: 301-305
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.433-435.301
• Online since: October 2013
• Authors: Bin Wen Huang, Yuan Jiao
• Keywords: Adaptive Threshold, Image De-Noising, Neighbor Dependency, Wavelet Packet Transform

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