Medical Image Denoising Using Mixed Transforms

Author:

Jameel Jaleel Sadoon

Abstract

 In this paper,  a mixed transform method is proposed based on a combination of wavelet transform (WT) and multiwavelet transform (MWT) in order to denoise medical images. The proposed method consists of WT and MWT in cascade form to enhance the denoising performance of image processing. Practically, the first step is to add a noise to Magnetic Resonance Image (MRI) or Computed Tomography (CT) images for the sake of testing. The noisy image is processed by WT to achieve four sub-bands and each sub-band is treated individually using MWT before the soft/hard denoising stage. Simulation results show that a high peak signal to noise ratio (PSNR) is improved significantly and the characteristic features are well preserved by employing mixed transform of WT and MWT due to their capability of separating noise signals from image signals. Moreover, the corresponding mean square error (MSE) is decreased accordingly compared to other available methods.

Publisher

University of Babylon

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Performance Analysis of the Edge-Preservation based Normalized Convolution for Medical Image Enhancement and Noise Reduction;2023 IEEE International Biomedical Instrumentation and Technology Conference (IBITeC);2023-11-09

2. Medical Image Transmission in 3D WiMAX Channel Using Adaptive Algorithm Based on MIMO-OFDM Principles;2023 Radiation and Scattering of Electromagnetic Waves (RSEMW);2023-06-26

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