Medical Image Denoising Based on Wavelet Soft Threshold Filting
Ping Xiong · Zhongguo yixue wulixue zazhi · 2009
Objective:To denoise digital radiographic images well. Methods: The paper presents a technique that uses the Anscombe's transformation to adjust the original image to a Gaussian noise model based upon the wavelet denoising method. The image is decomposed in different subbands of frequency and orientation and these coefficient are filted using different thresholds. Results: The proposed method that could keep images edges from damaging and increase PSNR is better than the whole wavelet denoising method. Conclusions: Quantitative and qualitative DR images assessment showed that the proposed algorithm outperforms the traditional Gaussian filter in terms of noise reduction, quality of details and bone sharpness.