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作 者:淡州阳 刘粉林[1] 巩道福[1] DAN Zhou-yang;LIU Fen-lin;GONG Dao-fu(School of Cybersapce Security,Information Engineering University,Zhengzhou 450001,China)
机构地区:[1]战略支援部队信息工程大学网络空间安全学院,郑州450001
出 处:《计算机科学》2021年第11期234-241,共8页Computer Science
基 金:国家自然科学基金(61772549,U1736214)。
摘 要:平滑处理是数字图像去噪和产生模糊效果的重要手段,经常被用于美化润饰“伪造”图像,因此对各种平滑滤波实施检测是十分有必要的。针对常见的图像平滑处理,文中提出了一种新的基于差分直方图中尾部信息的平滑滤波检测算法。首先,针对待检测图像,基于不同差分步长和方向构建多个差分绝对值直方图;然后,提取直方图中差分值为0和1的出现频率,以及直方图尾部从大到小若干个差分值及其出现频率构建多维检测特征;最后,构建SVM分类器对图像实施检测。在图像库中实施了平滑处理检测以及区分不同平滑滤波的实验,实验结果表明,所提算法对3种常见的空域平滑滤波(中值滤波、均值滤波、高斯滤波)均有优异的检测性能。此外,该算法能够有效地将平滑滤波与锐化、缩放、压缩等其他数字图像操作进行区分,并且在JPEG压缩图像中具有鲁棒性。Smoothing is an important method for digital image denoising and blurring.It is often used to beautify and retouch“forged”images.Therefore,it is necessary to detect various smoothing filters.Aiming at the common image smoothing processing,this paper proposes a new smoothing filter detection algorithm based on the tail information of differential histogram.Firstly,for the image to be detected,multiple difference absolute value histograms are constructed based on different difference step lengths and directions.Then,the occurrence frequency of the difference values of 0 and 1 in the histogram is extracted,and the several difference values from large to small at the tail of the histogram and their occurrence frequency are extracted to construct multi-dimensional detection feature.Finally,an SVM classifier is constructed to detect images.The experiments of smoothing detection and distinguishing different smoothing filters are carried out on the image library.The experimental results show that the proposed algorithm has excellent detection performance for three common spatial smoothing filters,including median filter,average filter and Gaussian filter.In addition,the algorithm can effectively distinguish smoothing filter from sharpening,scaling,compression and other digital image operations,and has robustness in JPEG compressed image.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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