Echocardiography image denoising using fractal wavelet transform

Authors

  • Reena Manandhar Department of Computer Engineering, Khwopa Engineering College, Libali-10, Bhaktapur, Nepal
  • Sanjeeb Prashad Pandey Department of Electronics and Communication Engineering, IOE, Pulchowk, Nepal

DOI:

https://doi.org/10.3126/jsce.v5i0.22369

Keywords:

Image denoising, wavelet transform, thresholding, Weiner filter, fractal wavelet transform

Abstract

One of the most important areas in image processing is medical image processing where the quality of the images has become an important issue. Most of the medical images are corrupted with the visual noise, and one of the such images is echocardiography image where this effect is more. So, this research aims to denoise the echocardiography image with fractal wavelet transform and to compare its performance with other wavelet based algorithm like hard thresholding, soft thresholding and wiener filter. Initially, the image is corrupted by the Gaussian noise with varying noise variances and is denoised using above mentioned different wavelet based denoising techniques. On comparison of the obtained results, it is observed that the fractal wavelet transform is well suited for highly degraded echocardiography images in terms of Mean Square Error (MSE) and Peak Signal To Noise Ratio (PSNR) than other wavelet based denoising methods. Further, the work could be enhanced to denoise the echocardiography image corrupted by other different types of noise. This research is limited to denoise the echocardiography image corrupted with Gaussian noise only.

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Published

2018-08-31

How to Cite

Manandhar, R., & Pandey, S. P. (2018). Echocardiography image denoising using fractal wavelet transform. Journal of Science and Engineering, 5, 23–33. https://doi.org/10.3126/jsce.v5i0.22369

Issue

Section

Research Papers