A New Adaptive Threshold Image-Denoising Method Based on Edge Detection

Yuan Jiao; Bin Wen Huang

doi:10.4028/www.scientific.net/AMM.678.137

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 678A New Adaptive Threshold Image-Denoising Method...

A New Adaptive Threshold Image-Denoising Method Based on Edge Detection

Abstract:

In image processing, removal of noise without blurring the image edges is a difficult problem. Aiming at orthogonal wavelet transform and traditional threshold’s shortage, a new wavelet packet transform adaptive threshold image de-noising method which is based on edge detection is proposed. By edge detection method, the wavelet packet coefficients corresponding to edge which is detected and other non-edge wavelet packet coefficients are treated by different threshold. Using the relativity among wavelet packet coefficients and neighbor dependency relation, at the same time, adopting the new variance neighbor estimate method and then the 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 image’s information and the quality after image de-noising is very well.

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Periodical:

Applied Mechanics and Materials (Volume 678)

Pages:

137-142

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.678.137

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Online since:

October 2014

Authors:

Yuan Jiao*, Bin Wen Huang

Keywords:

Edge Detection, Image Denoising, Neighbor Dependency Adaptive Threshold, Wavelet Packet Transform

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