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Contourlet Transform based Method for Medical Image Denoising
يروتنكلا ليوحتلا مادختساب ةيبطلا روصلا نم ءاضوضلا ةلازلإ ةقيرط

Author: Abbas Hanon Hassin AlAsadi يدسلاا نسح نونح سابع
Journal: Journal of Al-Qadisiyah for Computer Science and Mathematics مجلة القادسية لعلوم الحاسوب والرياضيات ISSN: 20740204 / 25213504 Year: 2015 Volume: 7 Issue: 1 Pages: 146-159
Publisher: Al-Qadisiyah University جامعة القادسية

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Abstract

Noise is an important factor of the medical image quality, because the high noise of medical imaging will not give us the useful information of the medical diagnosis. Basically, medical diagnosis is based on normal or abnormal information provided diagnose conclusion. In this paper, we proposed a denoising algorithm based on Contourlet transform for medical images. Contourlet transform is an extension of the wavelet transform in two dimensions using the multiscale and directional filter banks. The Contourlet transform has the advantages of multiscale and timefrequency-localization properties of wavelets, but also provides a high degree of directionality. For verifying the denoising performance of the Contourlet transform, two kinds of noise are added into our samples; Gaussian noise and Speckle noise. Soft thresholding value for the Contourlet coefficients of noisy image is computed. Finally, the experimental results of proposed algorithm are compared with the results of wavelet transform. We found that the proposed algorithm has achieved acceptable results compared with those achieved by wavelet transform.

ت ربتع لا لماوعلا مها نم )بئاوشلا( ءاضوضلا م كلذ يف ببسلا ىزعيو ، ةيبطلا روصلا ةدوج يف ةرثؤنا ىلا دوجو .ضارملال يبطلا صيخشتلا يف ةمعادلا ةمهملا تامولعملا ضعب يفخي دق ءاضوضلا نا املع.صيخشتلا يف يبطلا ريوصتلا ىلع دمتعت ضارملاا نم ريثكلايرط حارتقا مت ، ثحبلا اذه يف ليوحتلا مادختسا للاخ نم كلذو ةيبطلا روصلا نم ءاضوضلا ةلازلا ةقيجيوملا ليوحتلل ريوطتو عيسوت ليوحتلا اذه ربتعي ، ةقيقحلا يفو .يروتنكلا ( Wavelet ) ةيئانث روصلل( تاحشرملا نم نيعون ىلع يروتنكلا ليوحتلا دمتعي .داعبلاا Filters يمرهلا سلابلا حشرم لولاا : )( Laplacian pyramid يهاجتلاا حشرملا يناثلاو ) Directional filter) .)ةفاضا مت ، ةقيرطلا جئاتن نم ققحتللو ن امهو ، ةمدختسملا روصلا ىلا بئاوشلا نم نيعو Gaussian وSpeckle ( ةمعانلا ةبتعلا تدمتعا كلذكو . Soft threshold ) مت .يروتنكلا ليوحتلا تلاماعم دييحت يفققحتلا ةقيرط مادختساب جئاتنلا نم PSNR و SNR م جئاتنلا ةنراقم مت ذا ع اندجوو ، يجيوملا ليوحتلا جئاتن

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