Image watermarking based on Hessenberg decomposition and q-logarithmic transformation

Watermarking is essential for protecting digital copyright by deterring unauthorized use and asserting ownership of digital content such as images and videos. Robust image watermarking aims to embed information in a way that remains intact under various attacks, including noise addition, compression, and geometric transformations, while maintaining high visual quality. In this paper, we introduce a robust image watermarking technique that combines the q-logarithmic transform with Hessenberg decomposition. A quantization-based mechanism is utilized for watermark extraction. The effectiveness of the proposed method is assessed using a dataset of ten varied images and evaluated using the weight Peak Signal to Noise Ratio (wPSNR), Structural Similarity Index Measure (SSIM) and Normalized Correlation (NC) metrics. Experimental results show that our approach achieves superior robustness and extraction accuracy compared to existing techniques.