Abstract—Speckle is a multiplicative noise which decreases the quality of an ultrasound image. Thus speckle reduction has become a very essential exercise for diagnoses. A wavelet-based image denoising technique is an effective filter to reduce speckle. Homomorphic processing is an approach for wavelet filtering. In this approach, to convert multiplicative noise into additive noise, first logarithmic transform is performed, and then wavelet filtering and exponential operation are performed. In the non-homomorphic approach, wavelet filtering is applied directly to the speckled image without any log or exponential operation. The present study compares the non-homomorphic and the homomorphic wavelet filtering techniques for the speckled images. Quantitative and qualitative results demonstrate that the non-homomorphic technique has higher performance than the homomorphic technique.
Index Terms—Image denoising, speckle noise, ultrasonic imaging, wavelet filtering.
M. A. Gungor is with the Department of Electronics and Automation, Hitit University Vocational High School, 19169, Corum, Turkey (e-mail: alparslangungor@hitit.edu.tr).
I. Karagoz is with the Department of Electrical and Electronics Engineering, Faculty of Engineering, Gazi University, 06570, Ankara, Turkey (e-mail: irfankaragoz@gazi.edu.tr).
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Cite:M. A. Gungor and I. Karagoz, "Comparing Non-homomorphic and Homomorphic Wavelet Filtering Techniques for Speckled Images," International Journal of Computer Theory and Engineering vol. 8, no. 5, pp. 393-397, 2016.
