With the recent tremendous advances of computer graphics rendering and image editing technologies,computergenerated fake images,which in general do not reflect what happens in the reality,can now easily deceive the in...With the recent tremendous advances of computer graphics rendering and image editing technologies,computergenerated fake images,which in general do not reflect what happens in the reality,can now easily deceive the inspection of human visual system.In this work,we propose a convolutional neural network(CNN)-based model to distinguish computergenerated(CG)images from natural images(NIs)with channel and pixel correlation.The key component of the proposed CNN architecture is a self-coding module that takes the color images as input to extract the correlation between color channels explicitly.Unlike previous approaches that directly apply CNN to solve this problem,we consider the generality of the network(or subnetwork),i.e.,the newly introduced hybrid correlation module can be directly combined with existing CNN models for enhancing the discrimination capacity of original networks.Experimental results demonstrate that the proposed network outperforms state-of-the-art methods in terms of classification performance.We also show that the newly introduced hybrid correlation module can improve the classification accuracy of different CNN architectures.展开更多
Military image encryption plays a vital role in ensuring the secure transmission of sensitive visual information from unauthorized access.This paper proposes a new Tri-independent keying method for encrypting military...Military image encryption plays a vital role in ensuring the secure transmission of sensitive visual information from unauthorized access.This paper proposes a new Tri-independent keying method for encrypting military images.The proposed encryption method is based on multilevel security stages of pixel-level scrambling,bitlevel manipulation,and block-level shuffling operations.For having a vast key space,the input password is hashed by the Secure Hash Algorithm 256-bit(SHA-256)for generating independently deterministic keys used in the multilevel stages.A piecewise pixel-level scrambling function is introduced to perform a dual flipping process controlled with an adaptive key for obscuring the spatial relationships between the adjacent pixels.Adynamicmasking scheme is presented for conducting a bit-level manipulation based on distinct keys that change over image regions,providing completely different encryption results on identical regions.To handle the global correlation between large-scale patterns,a chaotic index-map system is employed for shuffling image regions randomly across the image domain based on a logistic map seeded with a private key.Experimental results on a dataset of military images show the effectiveness of the proposed encryption method in producing excellent quantitative and qualitative results.The proposed method obtains uniform histogram distributions,high entropy values around the ideal(≈8 bits),Number of Pixel Change Rate(NPCR)values above 99.5%,and low Peak Signal-to-Noise Ratio(PSNR)over all encrypted images.This validates the robustness of the proposed method against cryptanalytic attacks,verifying its ability to serve as a practical basis for secure image transmission in defense systems.展开更多
基金supported by the National Key Research and Development Program of China under Grant No.2019YFB2204104the Beijing Natural Science Foundation of China under Grant No.L182059+1 种基金the National Natural Science Foundation of China under Grant Nos.61772523,61620106003,and 61802406,Alibaba Group through Alibaba Innovative Research Programthe Joint Open Research Fund Program of State Key Laboratory of Hydroscience and Engineering and Tsinghua-Ningxia Yinchuan Joint Institute of Internet of Waters on Digital Water Governance.
文摘With the recent tremendous advances of computer graphics rendering and image editing technologies,computergenerated fake images,which in general do not reflect what happens in the reality,can now easily deceive the inspection of human visual system.In this work,we propose a convolutional neural network(CNN)-based model to distinguish computergenerated(CG)images from natural images(NIs)with channel and pixel correlation.The key component of the proposed CNN architecture is a self-coding module that takes the color images as input to extract the correlation between color channels explicitly.Unlike previous approaches that directly apply CNN to solve this problem,we consider the generality of the network(or subnetwork),i.e.,the newly introduced hybrid correlation module can be directly combined with existing CNN models for enhancing the discrimination capacity of original networks.Experimental results demonstrate that the proposed network outperforms state-of-the-art methods in terms of classification performance.We also show that the newly introduced hybrid correlation module can improve the classification accuracy of different CNN architectures.
文摘Military image encryption plays a vital role in ensuring the secure transmission of sensitive visual information from unauthorized access.This paper proposes a new Tri-independent keying method for encrypting military images.The proposed encryption method is based on multilevel security stages of pixel-level scrambling,bitlevel manipulation,and block-level shuffling operations.For having a vast key space,the input password is hashed by the Secure Hash Algorithm 256-bit(SHA-256)for generating independently deterministic keys used in the multilevel stages.A piecewise pixel-level scrambling function is introduced to perform a dual flipping process controlled with an adaptive key for obscuring the spatial relationships between the adjacent pixels.Adynamicmasking scheme is presented for conducting a bit-level manipulation based on distinct keys that change over image regions,providing completely different encryption results on identical regions.To handle the global correlation between large-scale patterns,a chaotic index-map system is employed for shuffling image regions randomly across the image domain based on a logistic map seeded with a private key.Experimental results on a dataset of military images show the effectiveness of the proposed encryption method in producing excellent quantitative and qualitative results.The proposed method obtains uniform histogram distributions,high entropy values around the ideal(≈8 bits),Number of Pixel Change Rate(NPCR)values above 99.5%,and low Peak Signal-to-Noise Ratio(PSNR)over all encrypted images.This validates the robustness of the proposed method against cryptanalytic attacks,verifying its ability to serve as a practical basis for secure image transmission in defense systems.
