Research on image denoising algorithm of joint bilateral filter and wavelet threshold shrinkage
Shangwang LIU1,2(), Liuyang GAO1,2, Bo WANG1,2
1.College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China 2.Engineering Lab of Intelligence Business and Internet of Things, Xinxiang 453007, China
ing at overcoming the shortcomings of existing denoising algorithms, such as the poor denoising capability, the noise error evaluation, and the damaging of the image edge and texture details, this paper proposes an image denoising algorithm of joint bilateral filter and wavelet threshold shrinkage. Firstly, the original noise image is divided into high-contrast and low-contrast layers by bilateral filter. Secondly, different appropriate filters are employed for different hierarchical layers. i.e., the bilateral filter and wavelet threshold shrinkage are adopted for high-contrast and low-contrast layers, respectively. Finally, the final denoising image is obtained by integrating high-contrast with low-contrast layers’ denoising images, which suppresses noises and at the same time enhances the image more efficiently. Experimental results show that peak signal to noise ratio (PSNR) of this method reaches 40.99 dB, which is higher than the ratio of non-local means filter, bilateral filter, wavelet threshold shrinkage and partial differential equation algorithms by 7.79%, 3.56%, 11.22% and 1.91%, respectively. Moreover, the proposed algorithm can not only remove the noises efficiently but also preserve the image edge and texture details very well.
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2018, Vol. 30 
), 郜刘阳1,2, 王博1,2
