斑点图案
人工智能
混响
散斑噪声
计算机科学
计算机视觉
GSM演进的增强数据速率
图像分割
分割
边缘检测
乙状窦函数
边缘增强
图像(数学)
模式识别(心理学)
图像处理
声学
物理
人工神经网络
作者
Huan Li,Jun Gao,Cheng‐Di Dong
摘要
This paper presents an adaptive edge enhancement algorithm for ultrasound imaging. Most of classical edge enhancement techniques take the whole image as a unit and use the spatial or frequency domain edge operators to enhance the region whose grey varies largely. Because of the speckle noises of the ultrasound images, edge operators may enhance the speckles and degrade the contrast resolution of the image. Moreover, classical edge enhancement techniques can enhance the reverberation artifacts which appear like the edge. In this paper we present a segmentation method, i.e. seeking the regions whose edges needs to be enhanced and ruling out the error edges caused either by speckle noises or the reverberation artifacts. Segmentation techniques are based on the texture analysis of the spatial grey level cooccurrence matrix. The proposed enhancement function is a class of modified sigmoid functions. Results show that we can leave speckle/reverberation unchanged and enhance tissue boundaries.
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