摘要
提出一种自适应选取各向异性扩散滤波器扩散参数的方法,以提高滤波器的有效性和稳定性。首先,使用最大类间方差二值化算法确定超声图像的最优二值化阈值,并将该阈值作为区域均匀性标准对超声图像进行四叉树分解。然后,按从大到小的顺序从分解结果中取出所有当前最大分块,根据最优同质区域分块判决依据进行优选。最后,使用最优同质区域选取结果计算扩散参数,对超声图像进行各向异性扩散滤波。结果表明,本方法优于斑点降噪各向异性扩散(SRAD)和细节保留各向异性扩散(DPAD)两种典型的自动选取扩散参数方法,能在显著减少运算时间的同时使平均图像佳数较前两种方法分别提高0.029和0.129。本方法避免了对人工同质区域选取的依赖,可准确计算扩散参数,在噪声消除和边缘保护上达到有效的平衡,是一种有效的超声图像降噪方法。
An adaptive selection method of diffusion threshold was proposed to improve the effectiveness and stability of a filter in speckle reduction of ultrasound images.An optimal threshold of the ultrasound image was determined by the Otsu binarization algorithm.Then,the ultrasound image was divided into blocks by Quad tree decomposition using the optimal threshold as the criterion of homogeneity.In descending order of the size,the present maximal blocks were picked up from the Quad tree decomposition result,and an optimal homogeneous region of the ultrasound image was selected by theproposed selection criteria.Finally,the diffusion threshold was obtained by analyzing statistical features of the optimal homogeneous region,and the ultrasound image was filtered using this diffusion threshold.The results demonstrate that the proposed method has better performance comparing with the Speckle Reducing Anisotropic Diffusion（SRAD）method and the Detail Preserving Anisotropic Diffusion（DPAD）method.It reduces the operation time effectively,and the average figure-of-merit by using the proposed method is 0.029,0.129higher than those by using other two mentioned methods. The proposed method avoids the manual selection of homogeneous area and can estimate the diffusion threshold accurately,which can reduce the speckles effectively while preserving the edges.
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2014年第5期1312-1321,共10页
Optics and Precision Engineering
基金
国家自然科学基金资助项目(No.61271071
No.11228411)
国家科技支撑计划资助项目(No.2012BAI13B02)
关键词
超声图像
斑点噪声
图像滤波
同质区域
各向异性扩散
ultrasound image
speckle noise
image filtering
homogeneous region
anisotropic diffusion
