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  • Open Access

    ARTICLE

    High-Secured Image LSB Steganography Using AVL-Tree with Random RGB Channel Substitution

    Murad Njoum1,2,*, Rossilawati Sulaiman1, Zarina Shukur1, Faizan Qamar1

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 183-211, 2024, DOI:10.32604/cmc.2024.050090 - 15 October 2024

    Abstract Random pixel selection is one of the image steganography methods that has achieved significant success in enhancing the robustness of hidden data. This property makes it difficult for steganalysts’ powerful data extraction tools to detect the hidden data and ensures high-quality stego image generation. However, using a seed key to generate non-repeated sequential numbers takes a long time because it requires specific mathematical equations. In addition, these numbers may cluster in certain ranges. The hidden data in these clustered pixels will reduce the image quality, which steganalysis tools can detect. Therefore, this paper proposes a… More >

  • Open Access

    ARTICLE

    Elevating Image Steganography: A Fusion of MSB Matching and LSB Substitution for Enhanced Concealment Capabilities

    Muhammad Zaman Ali1, Omer Riaz1, Hafiz Muhammad Hasnain2, Waqas Sharif2, Tenvir Ali2, Gyu Sang Choi3,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2923-2943, 2024, DOI:10.32604/cmc.2024.049139 - 15 May 2024

    Abstract In today’s rapidly evolving landscape of communication technologies, ensuring the secure delivery of sensitive data has become an essential priority. To overcome these difficulties, different steganography and data encryption methods have been proposed by researchers to secure communications. Most of the proposed steganography techniques achieve higher embedding capacities without compromising visual imperceptibility using LSB substitution. In this work, we have an approach that utilizes a combination of Most Significant Bit (MSB) matching and Least Significant Bit (LSB) substitution. The proposed algorithm divides confidential messages into pairs of bits and connects them with the MSBs of… More >

  • Open Access

    ARTICLE

    Image Denoising Using a Nonlinear Pixel-Likeness Weighted-Frame Technique

    P. Vinayagam1,*, P. Anandan2, N. Kumaratharan3

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 869-879, 2021, DOI:10.32604/iasc.2021.016761 - 20 August 2021

    Abstract Recent advances in the development of image denoising applications for eliminating the various sources of noise in digital images have employed hardware platforms based on field programmable gate arrays for attaining speed and efficiency, which are essential factors in real-time applications. However, image denoising providing for maximum denoising performance, speed, and efficiency on these platforms is subject to constant innovation. To this end, the present work proposes a high-throughput fixed-point adaptive edge noise filter architecture to denoise digital images with additive white Gaussian noise in realtime using a nonlinear modified pixel-likeness weighted-frame technique. The proposed More >

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