摘要
分析了水下散射图像的增量分布及自相似特性.针对传统分数布朗运动(FBM)模型存在的不足,基于分数列维稳定运动(FLSM)模型,将纹理表面的自相似指数看作依度量尺度而变化的变量,提出了一种新的多尺度分数列维稳定运动(MFLSM)模型,并将该模型扩展至二维用于对水下散射图像的仿真.仿真结果表明,该模型具有对纹理多尺度自相似性以及散斑纹理的表征能力.
This paper analyzes the increment distribution and self-similarity of typical underwater images. In order to overcome the disadvantages of the traditional fractal Brownian motion （FBM） model, a muhi-seale fractional Lévy stable-motion （MFLSM） model is proposed based on the fractional Lévy stable-motion （FLSM） model, in which the self-similarity parameter of image surface is considered as a variable to vary with the measure scale. The model is then extended to a 2D space and is further employed to simulate underwater scattering images. The results show that the proposed MFLSM model represents the multi-scale self-similarity and the speckle of underwater optical images well.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2008年第9期81-85,共5页
Journal of South China University of Technology(Natural Science Edition)
基金
国家“863”计划项目(2002AA401001-4B)
中国博士后科学基金资助项目(20070410823)
关键词
图像处理
散射图像
多尺度自相似性
稳定过程
image processing
scattering image
multi-scale self-similarity
stable process
