JPEG图像中的安全密写方案

JPEG是一种常见的图像格式,在JPEG图像中进行密写有着重要的实际意义。但以往的密写技术往往会改变载体图像的DCT系数直方图或增大分块效应,分析者可以据此察觉秘密信息的存在。为了提高密写安全性,该文提出一种新的JPEG密写方案。该方案在将秘密信息嵌入非0的非直流DCT系数时,既不改变原始图像的DCT系数直方图,也不增加载体图像的分块效应,因此可以抵抗基于直方图和基于分块特性的密写分析。实验表明,当载体图像的质量因子大于35时,秘密信息的安全性可以得到有效保证。     

Detection and localization of forgery using statistics of DCT and Fourier components

In this paper, we present a comprehensive approach for investigating JPEG compressed test images, suspected of being tampered either by splicing or copy-move forgery (cmf). In JPEG compression, the image plane is divided into non-overlapping blocks of size 8 × 8 pixels. A unified approach based on block-processing of JPEG image is proposed to identify whether the image is authentic/forged and subsequently localize the tampered region in forged images. In the initial step, doubly stochastic model (dsm) of block-wise quantized discrete cosine transform (DCT) coefficients is exploited to segregate authentic and forged JPEG images from a standard dataset (CASIA). The scheme is capable of identifying both the types of forged images, spliced as well as copy-moved. Once the presence of tampering is detected, the next step is to localize the forged region according to the type of forgery. In case of spliced JPEG images, the tampered region is localized using block-wise correlation maps of dequantized DCT coefficients and its recompressed version at different quality factors. The scheme is able to identify the spliced region in images tampered by pasting uncompressed or JPEG image patch on a JPEG image or vice versa, with all possible combinations of quality factors. Alternatively, in the case of copy-move forgery, the duplication regions are identified using highly localized phase congruency features of each block. Experimental results are presented to consolidate the theoretical concept of the proposed technique and the performance is compared with the already existing state of art methods.     

JPEG标准下图像压缩算法的研究与实现

介绍了基于DCT变换的JPEG图像压缩编码算法,提出了一种对DCT系数分级的方法,从而实现了JPEG码流的分级特性.     

一种基于JPEG图像的密写算法

目前,在基于JPEG图像的数字密写中,在保证隐蔽性和信息隐藏量的前提下,鲁棒性往往不能保证,导致提取秘密信息的正确率不够高。针对此,提出将汉明码应用于密写嵌入过程中,利用JPEG图像压缩原理,将处理后的隐蔽信息通过改变DCT系数来表示。通过实验分析与F4密写算法的比较,结果显示该方法具有较好的隐蔽性且具有较好的鲁棒性。     

针对一类JPEG图像伪造的被动盲取证

图像合成是一种最常见的图像伪造手段。该文针对一类JPEG图像合成伪造,根据篡改区域与非篡改区域块效应的不一致性,提出了一种简单有效的检测算法。首先利用估计的一次压缩质量因子对待检测图像进行裁剪再压缩,然后通过计算压缩前后的失真提取图像的块效应指数映射图,最后采用图像分割的方法实现篡改区域的自动检测与定位。实验结果表明,算法对于各种质量的JPEG图像和较小的篡改区域均能有效检测,当二次压缩与一次压缩的质量因子之差在15以上,虚警率控制在5%以内时,检测率可达93%以上。     

基于双混沌系统的抗JPEG压缩的图像认证水印算法

提出了一种新的兼具水印高安全性和高定位精度的抗JPEG压缩的图像认证水印算法.根据JPEG图像压缩过程中DCT系数的不变特性,将预先量化的DCT低频系数和水印密钥合成为混沌系统的初值.再将图像块的编号映射为混沌系统的迭代次数,经过logistic混沌迭代生成图像块水印.在水印嵌入过程中,利用另一混沌系统猫映射构造循环结构,建立图像块之间一一对应的循环关系,并将块水印嵌入到对应图像块的DCT中频系数中.实验结果表明,该算法对JPEG有损压缩具有良好的鲁棒性,同时可对图像内容的恶意篡改进行精确的检测与定位.     

结合集成比例训练的彩色JPEG图像隐写分析

该文提出一种YCbCr颜色空间的彩色JPEG图像隐写分析方法。该方法中的特征包括通道内特征和通道间特征,首先从Y通道提取Markov特征,扩展DCT特征以及共生矩阵特征构成通道内特征集合,通道内特征可以有效捕捉到Y通道内DCT系数之间的相关性;然后对Y通道进行下采样,从采样平面与CbCr平面相互之间的差分平面上提取特征构成通道间特征集合,通道间特征可以捕捉到两两通道之间的相关性。由于通道内特征和通道间特征在分类性能上有着较大差别,在分类阶段由通道内特征和通道间特征分别训练子分类器,通过调整两类子分类器的比例,使用多数投票方式来合成集成判决结果,最终获得最佳的检测性能。实验结果表明,该方法不仅适合小嵌入率的彩色JPEG图像,而且在性能上优于已有的JPEG图像隐写分析方法。     

整数型帧间差分JPEG算法及实现

本文对静态图象压缩标准JPEG进行了两方面改进，使之适用于运动序列的压缩，并易于在多媒体PC环境下实现．这两方面的改进是：帧间差分消除背景冗余；用CMT变换对DCT变换进行整数运算的逼近．最后给出了一些实验结果．     

JPEG encryption for image rescaling in the encrypted domain

This work proposes a novel protocol of encrypting the JPEG image suitable for image rescaling in the encrypted domain. To protect the privacy of original content, the image owner perturbs the texture and randomizes the structure of the JPEG image by enciphering the quantized Discrete Cosine Transform (DCT) coefficients. After receiving the encrypted JPEG image, the service provider generates a rescaled JPEG image by down-sampling the encrypted DCT coefficients. On the recipient side, the encrypted JPEG image rescaled by the service provider can be decrypted to a plaintext image with a lower resolution with the aid of encryption keys. Experimental results show that the proposed method has a good capability of rescaling the privacy-protected JPEG file.     

一种基于DCT域统计特征的JPEG图像隐写分析

提出了一种基于DCT域统计特征的JPEG图像隐写分析算法。该算法在分析JPEG图像的DCT域统计特性的基础上,提取了8维特征向量,通过LSSVM分类器对待测图像进行分类,以达到检测载密图像的目的。算法实现简单、计算复杂度低。实验结果表明,该算法检测速度快,具有较高的检测正确率,能够实现针对各类JPEG图像信息隐藏算法的有效检测。     

Image representation using block compressive sensing for compression applications

The emerging compressive sensing (CS) theory has pointed us a promising way of developing novel efficient data compression techniques, although it is proposed with original intention to achieve dimension-reduced sampling for saving data sampling cost. However, the non-adaptive projection representation for the natural images by conventional CS (CCS) framework may lead to an inefficient compression performance when comparing to the classical image compression standards such as JPEG and JPEG 2000. In this paper, two simple methods are investigated for the block CS (BCS) with discrete cosine transform (DCT) based image representation for compression applications. One is called coefficient random permutation (CRP), and the other is termed adaptive sampling (AS). The CRP method can be effective in balancing the sparsity of sampled vectors in DCT domain of image, and then in improving the CS sampling efficiency. The AS is achieved by designing an adaptive measurement matrix used in CS based on the energy distribution characteristics of image in DCT domain, which has a good effect in enhancing the CS performance. Experimental results demonstrate that our proposed methods are efficacious in reducing the dimension of the BCS-based image representation and/or improving the recovered image quality. The proposed BCS based image representation scheme could be an efficient alternative for applications of encrypted image compression and/or robust image compression.     

基于DCT系数统计特性的JPEG图像隐写分析

提出了一种基于离散余弦变换（DCT）系数统计特性的JPEG图像隐写分析算法。该算法在分析JPEG图像DCT系数的统计特性的基础上,提取了8维特征向量,通过最小二乘支持向量机（LS—SVM）分类器对待测图像进行分类,以达到检测载密图像的目的。算法实现简单,计算复杂度低。实验结果表明,该算法检测速度快,具有较高的检测正确率,能够实现针对各类JPEG图像信息隐写算法的有效检测。     

Adaptive JPEG steganography based on distortion cost updating

Previous adaptive JPEG steganography algorithms mostly calculate image distortion before secret information embedding,so they can’t dynamically adjust distortion costs.Considering the mutual impacts during embedding,an adaptive JPEG steganography algorithm based on distortion cost updating was proposed.Firstly,three factors that affect embedding fluctuations were analyzed,including quantization step,the absolute value of the quantized DCT coefficient to be modified and perturbation error.Then the embedding update strategy (EUS) was proposed,which enabled to dynamically update the distortion costs.After that,an adaptive JPEG steganography algorithm was implemented combining the strategy.The experimental result illustrates that the algorithm can significantly improve the secure performance of JPEG steganography algorithm.     

A novel deep learning framework for double JPEG compression detection of small size blocks

Double JPEG compression detection plays a vital role in multimedia forensics, to find out whether a JPEG image is authentic or manipulated. However, it still remains to be a challenging task in the case when the quality factor of the first compression is much higher than that of the second compression, as well as in the case when the targeted image blocks are quite small. In this work, we present a novel end-to-end deep learning framework taking raw DCT coefficients as input to distinguish between single and double compressed images, which performs superior in the above two cases. Our proposed framework can be divided into two stages. In the first stage, we adopt an auxiliary DCT layer with sixty-four 8 × 8 DCT kernels. Using a specific layer to extract DCT coefficients instead of extracting them directly from JPEG bitstream allows our proposed framework to work even if the double compressed images are stored in spatial domain, e.g. in PGM, TIFF or other bitmap formats. The second stage is a deep neural network with multiple convolutional blocks to extract more effective features. We have conducted extensive experiments on three different image datasets. The experimental results demonstrate the superiority of our framework when compared with other state-of-the-art double JPEG compression detection methods either hand-crafted or learned using deep networks in the literature, especially in the two cases mentioned above. Furthermore, our proposed framework can detect triple and even multiple JPEG compressed images, which is scarce in the literature as far as we know.     

一种保持直方图特性的JPEG图像掩密算法

传统的JPEG图像掩密算法往往因为改变了载体图像的DCT系数直方图而不能抵抗各种基于直方图的攻击,或者为了矫正直方图而降低了隐藏容量,该文提出一种新的保持直方图特性的算法。该算法在嵌入秘密消息时,动态建立Adjust_info表记录系数直方图被改变的情况,然后根据该表调整系数的变化方向,这样不但可以补偿直方图的改变,而且并不降低隐藏容量。对多幅图像的实验表明,该算法不但能够达到13%的高隐藏容量(压缩因子为75),而且掩密后图像总体DCT系数直方图的平均失真率为0.81%。由改进算法掩密后图像低频DCT系数直方图的最大失真率为3.83%,平均失真率只有1.98%,仅对直方图做了微小的改变,因此可以有效抵御各种直方图攻击,从而为安全掩密提供了可靠保证。     

JPEG2000码率控制算法的改进

针对在低码率时，脚2000编码中存在大量计算冗余，提出一种快速有效算法，该算法通过查表法快速估计斜率值并找到最佳截断点，这样不仅避免了斜率值的浮点除法运算，而且在低码率时，大量码块编码过程被丢弃，因此使EBCOT中层1编码的计算量大大减少。实验结果表明，该算法比PCRD算法的编码时间及存储器开销都大幅度下降，而重构图像质量相当。     

块级篡改定位的JPEG图像脆弱水印

 JPEG是一种常见的图像格式,在JPEG图像中进行准确的篡改定位具有重要意义. 本文提出一种新的JPEG图像脆弱水印方案,将每个小块主要内容的Hash比特重新分组,并将每组的模2和作为水印信息. 也就是说每一个小块都对应多个水印比特,每个水印比特也对应多个小块. 载体图像的每个小块中仅嵌入于1比特水印,保证了良好的隐蔽性. 认证时依据图像内容与水印比特的整体匹配情况估计篡改率,再根据每个小块对应的水印信息的被破坏程度判别该小块是否曾被篡改. 理论分析和实验结果标明该方法可以在篡改区域小于1%的情况下准确地找到所有篡改小块.     

用于图像认证的水印算法设计与硬件实现

为实现图像完整性认证,在分析现有各种脆弱水印算法的基础上,一种新的变换域脆弱水印算法被提出.该算法利用离散余弦变换(DCT)系数查表生成水印,嵌入的水印不可见性好,水印图像能有效检测各种攻击,具有良好的认证效果.此外该算法适用于硬件实现,且能方便地嵌入到现有的JPEG压缩器中,具有速度快、面积小的特点.     

一种动态精度匹配的面积优化2-D DCT/IDCT的实现

提出了一种JPEG标准推荐的2—DDCT／IDCT的改进型Loeffler算法的ASIC实现。该设计采用硬件复用的方法，在正向和反向变换过程中使用同一运算电路，达到了面积优化的目的；并对输入数据进行系数预判，在特定输入情况下，有效提高了处理速度和降低功耗；还根据JPEG体系结构，在DCT变换和量化器之间建立劝态的精度匹配，保证了不同压缩比下的图像质量和功耗效率。该电路应用于140万像素数码相机的JPEG图像处理ASIC芯片中，已成功通过了FPGA验证和流片测试。     

A novel blind robust image watermarking in DCT domain using inter-block coefficient correlation

This paper presents a novel blind watermarking algorithm in DCT domain using the correlation between two DCT coefficients of adjacent blocks in the same position. One DCT coefficient of each block is modified to bring the difference from the adjacent block coefficient in a specified range. The value used to modify the coefficient is obtained by finding difference between DC and median of a few low frequency AC coefficients and the result is normalized by DC coefficient. The proposed watermarking algorithm is tested for different attacks. It shows very good robustness under JPEG image compression as compared to existing one and also good quality of watermark is extracted by performing other common image processing operations like cropping, rotation, brightening, sharpening, contrast enhancement etc.