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<p>This paper presents a new hybrid method for concealing images within a cover image using Integer Wavelet Transform and Singular Value Decomposition to enhance the imperceptibility and robustness of hidden images within a cover image. A custom graphical user interface has been developed to aid in evaluating performance metrics, allowing users to assess how various noise conditions affect stego images interactively. The technique shows minimal distortion with a Mean Squared Error of 9.6698 and a Bit Error Rate of 0.7205. Both the Structural Similarity Index Measure and Normalised Cross-Correlation are close to 1 while achieving a Peak Signal-to-Noise Ratio of 29.5665&#xa0;dB. Our results surpass current methods, particularly when gauging resilience under noise such as Gaussian, speckle, and salt and pepper, proving that this proposed technique effectively maintains high image quality and steganographic security. The results establish the method’s potential for secure image transmission in applications such as defense communications, medical image confidentiality, forensic authentication, and digital rights protection, while providing a reproducible platform for future steganographic research.</p>

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Analysis of hybrid integer wavelet transform and singular value decomposition for image steganography under various noise conditions

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月27日

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  • Manikandan Chinnusami,
  • Dyutisri Kolli,
  • S. Shreela,
  • Rajesh Anbazhagan,
  • Rengarajan Amirtharajan

摘要

This paper presents a new hybrid method for concealing images within a cover image using Integer Wavelet Transform and Singular Value Decomposition to enhance the imperceptibility and robustness of hidden images within a cover image. A custom graphical user interface has been developed to aid in evaluating performance metrics, allowing users to assess how various noise conditions affect stego images interactively. The technique shows minimal distortion with a Mean Squared Error of 9.6698 and a Bit Error Rate of 0.7205. Both the Structural Similarity Index Measure and Normalised Cross-Correlation are close to 1 while achieving a Peak Signal-to-Noise Ratio of 29.5665 dB. Our results surpass current methods, particularly when gauging resilience under noise such as Gaussian, speckle, and salt and pepper, proving that this proposed technique effectively maintains high image quality and steganographic security. The results establish the method’s potential for secure image transmission in applications such as defense communications, medical image confidentiality, forensic authentication, and digital rights protection, while providing a reproducible platform for future steganographic research.