B-mode ultrasonic images quality enhancement using an intelligent 5∗5 pixels window averaging

Image processing has been widely utilized in different areas including artificial intelligent, medical image processing, robotics and etc. In this paper, a novel approach to reduce the speckle noise from ultrasound images is proposed. Ultrasound imaging devices are the most commonly used imaging systems in medical field. Although, the main negative side of these imaging techniques is speckle noise, which is an inherent nature of ultrasound images. Despeckling ultrasound images has captured attention of scientists for many decades. In this present study, a non-uniform averaging filter is suggested. Intelligent window averaging (IWA) filter as the proposed method considers a 5 × 5 window size and defines a specific range. It computes the average value of pixels within the kernel existing in this range. Then, it switches the average value with the centered cell. Furthermore, the new algorithm is validated through real B-mode ultrasonic images. Eventually, the proposed approach is compared with other state-of-the-art despeckling methods to demonstrate its better performance.

[1]  R. Sivakumar,et al.  Speckle filtering of ultrasound B-Scan Images - a comparative study between spatial and diffusion filters , 2010, 2010 IEEE Conference on Open Systems (ICOS 2010).

[2]  Deepika,et al.  De-speckling of Medical Ultrasound Images using Wiener Filter and Wavelet Transform , .

[3]  P. Nageswari,et al.  A comparative study of despeckling filters for enhancement of medical images , 2017, 2017 Conference on Emerging Devices and Smart Systems (ICEDSS).

[4]  Scott T. Acton,et al.  Ultrasound Despeckling for Contrast Enhancement , 2010, IEEE Transactions on Image Processing.

[5]  H. Chenga,et al.  Automated breast cancer detection and classification using ultrasound images A survey , 2009 .

[6]  Silvana G. Dellepiane,et al.  Quality Assessment of Despeckled SAR Images , 2011, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[7]  C. Chandrasekar,et al.  Speckle Noise Reduction of Medical Ultrasound Images using Bayesshrink Wavelet Threshold , 2011 .

[8]  P. M. Shivakumara Swamy,et al.  A novel thresholding technique in the curvelet domain for improved speckle removal in SAR images , 2016 .

[9]  Yanbo Li,et al.  Speckle Noise Suppression Techniques for Ultrasound Images , 2009, 2009 Fourth International Conference on Internet Computing for Science and Engineering.

[10]  G. R. Suresh,et al.  Speckle Noise Reduction in Ultrasound Images by Wavelet Thresholding based on Weighted Variance , 2009 .

[11]  Manish Khare,et al.  Despeckling of medical ultrasound images using Daubechies complex wavelet transform , 2010, Signal Process..

[12]  Manpreet Kaur,et al.  Survey of Despeckling Techniques for Medical Ultrasound Images , 2011 .

[13]  Kie B Eom,et al.  Speckle reduction in ultrasound images using nonisotropic adaptive filtering. , 2011, Ultrasound in medicine & biology.

[14]  Antonio Fernández-Caballero,et al.  Finding out general tendencies in speckle noise reduction in ultrasound images , 2009, Expert Syst. Appl..

[15]  Dhanalakshmi Srinivasan,et al.  A View on Despeckling in Ultrasound Imaging , 2009 .

[16]  Yingtao Zhang,et al.  A novel approach to speckle reduction in ultrasound imaging. , 2009, Ultrasound in medicine & biology.

[17]  Ms. Alka Vishwa,et al.  Speckle Noise Reduction in Ultrasound Images by Wavelet Thresholding , 2012 .

[18]  Faouzi Benzarti,et al.  Speckle Noise Reduction in Medical Ultrasound Images , 2013, ArXiv.

[19]  Wai-kuen Cham,et al.  Image postprocessing by Non-local Kuan's filter , 2011, J. Vis. Commun. Image Represent..

[20]  Ping Sun,et al.  An improved windowed Fourier transform filter algorithm , 2015 .

[21]  M. A. Yousuf,et al.  A New Method to Remove Noise in Magnetic Resonance and Ultrasound Images , 2010 .

[22]  Giampaolo Ferraioli,et al.  Enhanced wiener filter for desplecking ultra-sound images , 2016, 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop (NSS/MIC/RTSD).

[23]  R. Sivakumar,et al.  Despeckling of Ultrasound Medical Images: A Survey , 2013 .

[24]  Mario Mastriani,et al.  Kalman's shrinkage for wavelet-based despeckling of SAR images , 2008, ArXiv.

[25]  G. V. Gavriloaia,et al.  Anisotropic Diffusion and Wavelet Filtering of Ultrasound Images , 2011 .