A Deep Belief Network-Based Robust Image Watermarking Method Using Modified Dual-Tree Complex Wavelet Transform and OTP Encryption

Digital image watermarking, which covertly embeds information within photos while maintaining their visual quality, is essential to protecting intellectual property. This study introduces a new method for image watermarking that makes use of enhanced One-Time Pad (OTP) encryption and the Modified Dual-Tree Complex Wavelet Transform (DT-CWT). The technique guarantees safe watermark extraction and insertion in cover photos while remaining resilient to possible intrusions. The cover image is divided into four parts during the embedding phase. Singular Value Decomposition (SVD) and Modified DT-CWT are then used for effective frequency domain embedding, and improved OTP encryption is used for increased security. Additionally, Modified Arnold Scrambling’s key generation is aided by a Deep Belief Network (DBN), which increases security. Inverse processes of Modified Arnold Scrambling and SVD are used to recover the watermark intact during extraction, whereas inverse processes of Modified DT-CWT, SVD, and OTP decryption are used to recover the original cover image. The DBN approach for Dataset[Formula: see text]1 produces an SSIM of 0.812, which shows that the image’s structure is strongly preserved even after compression. With an SSIM of 0.758 in Dataset[Formula: see text]2, the DBN approach once more outperforms traditional methods such as DNN (0.705), GRU (0.670), and LSTM (0.669).

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Publication Details

Journal
International Journal of Image and Graphics
Published
2025-12-11
DOI
https://doi.org/10.1142/s0219467827500793
Primary Topic
Advanced Steganography and Watermarking Techniques
Type
article
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article

A Deep Belief Network-Based Robust Image Watermarking Method Using Modified Dual-Tree Complex Wavelet Transform and OTP Encryption

Ramesh Shelke, Manuj Joshi, Mangalagowri Gorbal, Dilendra Hiran
International Journal of Image and Graphics
Advanced Steganography and Watermarking Techniques
article

A Deep Belief Network-Based Robust Image Watermarking Method Using Modified Dual-Tree Complex Wavelet Transform and OTP Encryption

Ramesh Shelke, Manuj Joshi, Mangalagowri Gorbal, Dilendra Hiran
article en

Abstract

Digital image watermarking, which covertly embeds information within photos while maintaining their visual quality, is essential to protecting intellectual property. This study introduces a new method for image watermarking that makes use of enhanced One-Time Pad (OTP) encryption and the Modified Dual-Tree Complex Wavelet Transform (DT-CWT). The technique guarantees safe watermark extraction and insertion in cover photos while remaining resilient to possible intrusions. The cover image is divided into four parts during the embedding phase. Singular Value Decomposition (SVD) and Modified DT-CWT are then used for effective frequency domain embedding, and improved OTP encryption is used for increased security. Additionally, Modified Arnold Scrambling’s key generation is aided by a Deep Belief Network (DBN), which increases security. Inverse processes of Modified Arnold Scrambling and SVD are used to recover the watermark intact during extraction, whereas inverse processes of Modified DT-CWT, SVD, and OTP decryption are used to recover the original cover image. The DBN approach for Dataset[Formula: see text]1 produces an SSIM of 0.812, which shows that the image’s structure is strongly preserved even after compression. With an SSIM of 0.758 in Dataset[Formula: see text]2, the DBN approach once more outperforms traditional methods such as DNN (0.705), GRU (0.670), and LSTM (0.669).

International Journal of Image and Graphics
Pacific Dental College and Hospital (IN)
Openalex Percentile: Top 59%
Advanced Steganography and Watermarking Techniques
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