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An Enhanced Gray-Scale Digital Watermarking Approach Utilizing Discrete Wavelet Transform and Reed-Solomon Error Correction

Monia Abdullah Ahmed Al-Hobishi · Nabil Mohammed Ali Munassar · Muhammed Fadhl Abdullah
10.20428/jst.v30i8.2997 387 Views 0 Citations
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Abstract

Digital watermarking has become essential for protecting intellectual property and ensuring content authenticity in the digital age. However, a significant challenge remains in developing watermarking techniques that are both robust against various attacks (such as compression, noise, and cropping) and imperceptible to the human eye, which is crucial for maintaining the quality of the original content. This paper addresses these challenges by proposing an advanced digital image watermarking technique that combines a three-level Discrete Wavelet Transform (DWT) using the Haar wavelet family with Reed-Solomon (RS) error-correcting codes. The three-level DWT decomposes the image into multiple frequency components, allowing the watermark to be embedded in the most significant parts of the image, thereby enhancing robustness. The integration of Reed-Solomon codes over finite fields further increases the watermark's resilience, enabling recovery even when parts of the watermark are damaged or lost due to attacks. Experimental results demonstrate that the proposed approach significantly improves watermark performance, with Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) showing substantial gains. The combination of Haar-based DWT and Reed-Solomon codes improves the watermark's robustness by up to 27 times compared to traditional methods without error correction. This approach provides a promising solution for secure, efficient, and reliable digital watermarking in applications requiring high robustness and content integrity.

Cite this Article (APA)
Monia, A. A. A., Nabil, M. A. M., Muhammed, F. A. (2025). An Enhanced Gray-Scale Digital Watermarking Approach Utilizing Discrete Wavelet Transform and Reed-Solomon Error Correction. Journal of Science and Technology. https://doi.org/10.20428/jst.v30i8.2997
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Published in
ISSN 1607-2073
Quartile Q1
AMS Score 100
Field Natural Sciences
Publisher University of Science and Technolog
Country 🇾🇪 Yemen
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Authors
Publication Details
Year 2025
Language English/Arabic
Added 13 Aug 2026