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Search Results (13)
  • Open Access

    ARTICLE

    Restoration of the JPEG Maximum Lossy Compressed Face Images with Hourglass Block-GAN

    Jongwook Si1, Sungyoung Kim2,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2893-2908, 2024, DOI:10.32604/cmc.2023.046081

    Abstract In the context of high compression rates applied to Joint Photographic Experts Group (JPEG) images through lossy compression techniques, image-blocking artifacts may manifest. This necessitates the restoration of the image to its original quality. The challenge lies in regenerating significantly compressed images into a state in which these become identifiable. Therefore, this study focuses on the restoration of JPEG images subjected to substantial degradation caused by maximum lossy compression using Generative Adversarial Networks (GAN). The generator in this network is based on the U-Net architecture. It features a new hourglass structure that preserves the characteristics of the deep layers. In… More >

  • Open Access

    ARTICLE

    High-Imperceptibility Data Hiding Scheme for JPEG Images Based on Direction Modification

    Li Liu1, Jing Li1, Yingchun Wu1, Chin-Chen Chang2,*, Anhong Wang1

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1415-1432, 2023, DOI:10.32604/csse.2023.040039

    Abstract Data hiding (DH) is an important technology for securely transmitting secret data in networks, and has increasing become a research hotspot throughout the world. However, for Joint photographic experts group (JPEG) images, it is difficult to balance the contradiction among embedded capacity, visual quality and the file size increment in existing data hiding schemes. Thus, to deal with this problem, a high-imperceptibility data hiding for JPEG images is proposed based on direction modification. First, this proposed scheme sorts all of the quantized discrete cosine transform (DCT) block in ascending order according to the number of non-consecutive-zero alternating current (AC) coefficients.… More >

  • Open Access

    ARTICLE

    A Deep Learning Driven Feature Based Steganalysis Approach

    Yuchen Li1, Baohong Ling1,2,*, Donghui Hu1, Shuli Zheng1, Guoan Zhang3

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2213-2225, 2023, DOI:10.32604/iasc.2023.029983

    Abstract The goal of steganalysis is to detect whether the cover carries the secret information which is embedded by steganographic algorithms. The traditional steganalysis detector is trained on the stego images created by a certain type of steganographic algorithm, whose detection performance drops rapidly when it is applied to detect another type of steganographic algorithm. This phenomenon is called as steganographic algorithm mismatch in steganalysis. To resolve this problem, we propose a deep learning driven feature-based approach. An advanced steganalysis neural network is used to extract steganographic features, different pairs of training images embedded with steganographic algorithms can obtain diverse features… More >

  • Open Access

    REVIEW

    An Overview of Double JPEG Compression Detection and Anti-detection

    Kun Wan*

    Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 89-101, 2022, DOI:10.32604/jihpp.2022.039764

    Abstract JPEG (Joint Image Experts Group) is currently the most widely used image format on the Internet. Existing cases show that many tampering operations occur on JPEG images. The basic process of the operation is that the JPEG file is first decompressed, modified in the null field, and then the tampered image is compressed and saved in JPEG format, so that the tampered image may be compressed several times. Therefore, the double compression detection of JPEG images can be an important part for determining whether an image has been tampered with, and the study of double JPEG compression anti-detection can further… More >

  • Open Access

    ARTICLE

    Detecting Double JPEG Compressed Color Images via an Improved Approach

    Xiaojie Zhao1, Xiankui Meng1, Ruyong Ren2, Shaozhang Niu2,*, Zhenguang Gao3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1765-1781, 2023, DOI:10.32604/cmc.2023.029552

    Abstract Detecting double Joint Photographic Experts Group (JPEG) compression for color images is vital in the field of image forensics. In previous researches, there have been various approaches to detecting double JPEG compression with different quantization matrices. However, the detection of double JPEG color images with the same quantization matrix is still a challenging task. An effective detection approach to extract features is proposed in this paper by combining traditional analysis with Convolutional Neural Networks (CNN). On the one hand, the number of nonzero pixels and the sum of pixel values of color space conversion error are provided with 12-dimensional features… More >

  • Open Access

    ARTICLE

    Analytic Beta-Wavelet Transform-Based Digital Image Watermarking for Secure Transmission

    Hesham Alhumyani1,*, Ibrahim Alrube1, Sameer Alsharif1, Ashraf Afifi1, Chokri Ben Amar1, Hala S. El-Sayed2, Osama S. Faragallah3

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4657-4673, 2022, DOI:10.32604/cmc.2022.020338

    Abstract The rapid development in the information technology field has introduced digital watermark technologies as a solution to prevent unauthorized copying and redistribution of data. This article introduces a self-embedded image verification and integrity scheme. The images are firstly split into dedicated segments of the same block sizes. Then, different Analytic Beta-Wavelet (ABW) orthogonal filters are utilized for embedding a self-segment watermark for image segment using a predefined method. ABW orthogonal filter coefficients are estimated to improve image reconstruction under different block sizes. We conduct a comparative study comparing the watermarked images using three kinds of ABW filters for block sizes… More >

  • Open Access

    ARTICLE

    CNN-Based Forensic Method on Contrast Enhancement with JPEG Post-Processing

    Ziqing Yan1,2, Pengpeng Yang1,2, Rongrong Ni1,2,*, Yao Zhao1,2, Hairong Qi3

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3205-3216, 2021, DOI:10.32604/cmc.2021.020324

    Abstract As one of the most popular digital image manipulations, contrast enhancement (CE) is frequently applied to improve the visual quality of the forged images and conceal traces of forgery, therefore it can provide evidence of tampering when verifying the authenticity of digital images. Contrast enhancement forensics techniques have always drawn significant attention for image forensics community, although most approaches have obtained effective detection results, existing CE forensic methods exhibit poor performance when detecting enhanced images stored in the JPEG format. The detection of forgery on contrast adjustments in the presence of JPEG post processing is still a challenging task. In… More >

  • Open Access

    ARTICLE

    Compression of Grayscale Images in DRPE-based Encrypted Domain

    Osama S. Faragallah1,*, Ensherah A. Naeem2, Hala S. Elsayed3, Fathi E. Abd El-Samie4

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 1019-1031, 2021, DOI:10.32604/iasc.2021.019185

    Abstract Compressing the encrypted images is considered an important issue in many applications such as cloud computing. From this perspective, this paper introduces an efficient approach for compression processing of images in the encrypted domain. The images are optically encrypted using the Double Random Phase Encoding (DRPE). The Joint Photographic Experts Group (JPEG) and the Set Partitioning in Hierarchical Trees (SPIHT) compression schemes have been used to compress the encrypted images. The process starts by converting the original image into an optical signal by an optical emitter like an optical source and encrypting it with DRPE. The DRPE applies two-phase modulations… More >

  • Open Access

    ARTICLE

    OPPR: An Outsourcing Privacy-Preserving JPEG Image Retrieval Scheme with Local Histograms in Cloud Environment

    Jian Tang, Zhihua Xia*, Lan Wang, Chengsheng Yuan, Xueli Zhao

    Journal on Big Data, Vol.3, No.1, pp. 21-33, 2021, DOI:10.32604/jbd.2021.015892

    Abstract As the wide application of imaging technology, the number of big image data which may containing private information is growing fast. Due to insufficient computing power and storage space for local server device, many people hand over these images to cloud servers for management. But actually, it is unsafe to store the images to the cloud, so encryption becomes a necessary step before uploading to reduce the risk of privacy leakage. However, it is not conducive to the efficient application of image, especially in the Content-Based Image Retrieval (CBIR) scheme. This paper proposes an outsourcing privacypreserving JPEG CBIR scheme. We… More >

  • Open Access

    ARTICLE

    Multiple Images Steganography of JPEG Images Based on Optimal Payload Distribution

    Yang Pei1,2, Xiangyang Luo1,2,*, Yi Zhang2, Liyan Zhu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 417-436, 2020, DOI:10.32604/cmes.2020.010636

    Abstract Multiple images steganography refers to hiding secret messages in multiple natural images to minimize the leakage of secret messages during transmission. Currently, the main multiple images steganography algorithms mainly distribute the payloads as sparsely as possible in multiple cover images to improve the detection error rate of stego images. In order to enable the payloads to be accurately and efficiently distributed in each cover image, this paper proposes a multiple images steganography for JPEG images based on optimal payload redistribution. Firstly, the algorithm uses the principle of dynamic programming to redistribute the payloads of the cover images to reduce the… More >

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