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Efficient image steganography method using contourlet transform and geometric-based pixel encryption for enhanced security
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  • Published: 09 April 2026

Efficient image steganography method using contourlet transform and geometric-based pixel encryption for enhanced security

  • Rajesh Kumar1,
  • Sunita Singhal1 &
  • Vijay Kumar Sharma1 

Scientific Reports (2026) Cite this article

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  • Engineering
  • Mathematics and computing

Abstract

In recent years, the transmission of multimedia content has become an essential aspect of information security. Information security can be divided into two essential components: content hiding and cryptography. For secure communication, both content hiding and cryptography are essential. In the proposed research, the combination of steganography with image pixel value encryption techniques has been demonstrated to enhance security. Before the embedding operation, the secret images are encrypted to improve the confidentiality of the hidden image. Encryption operation is performed using the Geometric Mean that includes “Arithmetic Progression (AP), Harmonic Progression (HP) and Geometric Progression (GP)” applied to “Secret Image”. Embedding is then carried out using the Contourlet Transform (CT) to ensure better visual quality of the stego image. The presented approach utilises a Laplacian Pyramidal Directional Filter Bank (LPDFB). Laplacian pyramids capture contours from the image and craft a linear structure using a Directional Filter Bank (DFB). Experimental results confirm that the proposed double-layer encryption-based steganography technique functions as a robust image embedding scheme, providing high imperceptibility while preserving the integrity of the secret image under various attacks, similar to a robust watermarking approach. Several types of security outbreaks, including noise tampering, compression-based tampering, rotational alterations, and cropping-based alterations, were performed on stego images and recovered extracted secret images. The average experimental results of the proposed technique achieved 45.5 dB (decibels) Peak to Signal Noise Ratio (PSNR), 0.9837 Structural Similarity Index (SSIM), 0.0020 Bit Error Rate (BER) and 0.9951 Normalized Correlation Coefficient (NCC), which is better than existing methods. The generated high-quality stego image is secured against various steganalysis tampered conditions.

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Data availability

The datasets analyzed during the current study are available in the USC SIPI Image Database at https://sipi.usc.edu/database/database.php? volume=misc.

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Acknowledgements

This paper discusses an Efficient image steganography Technique for secure communication.

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Open access funding provided by Manipal University Jaipur. All the funding is supported by Manipal University Jaipur.

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  1. Manipal University Jaipur, Jaipur, India

    Rajesh Kumar, Sunita Singhal & Vijay Kumar Sharma

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  2. Sunita Singhal
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Rajesh has designed and developed the Algorithm, Dr Sunita Singhal and Dr Vijay Kumar Sharma helped to write and proof read the work.

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Correspondence to Sunita Singhal or Vijay Kumar Sharma.

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Kumar, R., Singhal, S. & Sharma, V.K. Efficient image steganography method using contourlet transform and geometric-based pixel encryption for enhanced security. Sci Rep (2026). https://doi.org/10.1038/s41598-026-41168-0

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  • Received: 11 July 2025

  • Accepted: 18 February 2026

  • Published: 09 April 2026

  • DOI: https://doi.org/10.1038/s41598-026-41168-0

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Keywords

  • Contourlet Transform
  • Geometric Mean
  • Directional Filter Bank
  • Multiscale Decomposition
  • Cyber bullies
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