基于多特征差异检测与联合控制映射的红外图像选择加密算法

Infrared image selective encryption algorithm based on multi-featuredifference detection and joint control mapping

  • 摘要: 为了实现对红外图像的选择性加密,提出了基于多特征差异检测与联合控制映射的红外图像选择算法。引入分段正弦变换,将输出图像分割为3个不同的区域,对每个区域完成不同的拉伸变换,完成初始红外图像的增强,凸显真实红外目标;再利用增强图像中目标与背景的灰度差异,从而设计目标决策因子,并分割Top-Hat变换的结构元素,构建红外背景抑制机制,过滤杂波与噪声;利用灰度水平、对比度与相似度,建立多特征差异检测模型,提取包含真实目标与可疑目标的感兴趣区域;以Logistic映射为控制条件,综合Tent映射与Chebyshev映射,设计联合控制混沌映射,利用其输出的混合随机序列对感兴趣区域进行置乱;引入引力模型,对混淆的感兴趣区域内的像素进行扩散,完成红外目标选择加密。实验结果显示:与已有的图像局部加密机制相比,该文算法输出密文信息熵值达到了7.982 6,能够更好地用于红外图像局部选择性加密。

     

    Abstract: In order to realize selective encryption of infrared images, an infrared image selection algorithm based on multi-feature difference detection and joint control mapping is proposed. Initial infrared image is enhanced by introducing segmented Sine transform to highlight true infrared target. Then target decision factor is designed by considering gray difference between target and background, and infrared background suppression mechanism is constructed by segmenting structure elements of Top-Hat transform to filter clutter and noise. Multi-feature difference detection model is established by using gray level, contrast and similarity degree to extract region of interest of real target and suspicious object. Joint control chaotic mapping is designed by Logistic map, Tent map and chebysbev map to permutation region of interest. Finally, gravity model is introduced to spread pixels in region of interest for complete infrared target selection encryption. Experimental results show that compared with existing local encryption mechanism, entropy of cipher text information is 7.982 6, which can be used for local selective encryption of infrared images.

     

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