Quantum-inspired Despeckling of Medical Ultrasound Images Based on Local Entropy
Fu Xiao-wei Dai Yun Chen Li Tian Jing Ding Sheng
(College of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430065, China)
(Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan 430065, China)
Abstract：Aiming at the limitation of existing methods for the medical ultrasound images despeckling, a novel quantum-inspired despeckling method based on the local entropy is proposed for the medical ultrasound images. Firstly, the log-transformed images are decomposed by the Dual-tree Complex Wavelet Transform (DTCWT), and the signal and speckle noise are modeled separately. Then, considering the normalized products of the local entropy of the real components extracted from coefficients and their parents, the adjustable parameter is obtained by the quantum inspired theory to adjust the probability of signal and noise. Finally, the modified bivariate shrinkage function is exploited to obtain the despeckled image. The experimental results show that the proposed method can preserve detail information effectively and reduce the speckle noise of medical ultrasound image at the same time.
付晓薇, 代芸, 陈黎, 田菁, 丁胜. 基于局部熵的量子衍生医学超声图像去斑[J]. 电子与信息学报, 2015, 37(3): 560-566.
Fu Xiao-Wei, Dai Yun, Chen Li, Tian Jing, Ding Sheng. Quantum-inspired Despeckling of Medical Ultrasound Images Based on Local Entropy. , 2015, 37(3): 560-566.
2015, Vol. 37 
