Hyperspectral remote sensing image watermarking using discrete wavelet transform and forensic based investigation archimedes optimization

• Published in: Earth science informatics 2024-10, Vol.17 (5), p.4297-4313
• Main Authors: Bodke, Minal, Chaudhari, Sangita
• Format: Article
• Language: English
• Subjects: Algorithms; Banded structure; Discrete Wavelet Transform; Earth and Environmental Science; Earth Sciences; Earth System Sciences; Embedding; Image quality; Image transmission; Information Systems Applications (incl.Internet); Noise levels; Ontology; Optimization; Position (location); Remote sensing; Satellite communications; Satellite imagery; Satellites; Signal to noise ratio; Simulation and Modeling; Space Exploration and Astronautics; Space Sciences (including Extraterrestrial Physics; Watermarking; Wavelet transforms
• ISSN: 1865-0473; 1865-0481
• DOI: 10.1007/s12145-024-01394-4

Rapid advancement in satellite communication over the last decade have resulted in the widespread use of remote sensing images. Additionally, as satellite image transmission over the Internet has increased, secrecy concerns have also arisen. As a result, digitally transmitted images must have great imperceptibility and confidentiality. Multispectral images consist of multiple bands. It is very challenging to select the important spectral band for watermarking so that the structural and visual quality of the satellite Image can be retained. This work proposes an innovative blind watermarking model based on a hybrid optimization strategy performed with the following two processes: the embedding process and the extraction process. A novel hybrid optimization named FBIAO algorithm, which is the amalgamation of Archimedes Optimization (ArchOA) and Forensic Based Investigation Optimization (FBIO) algorithm is used to select spectral band for watermarking. The proposed novel FBIAO enhances the balances between the exploration and exploitation, boosts the solution diversity and improves the convergence of FBI based optimization for spectral band selection. The 3-level Discrete Wavelet Transform (DWT) is used to embed the watermark logo in the selected spectral band image and then position selection is applied to identify the location for embedding the watermark. Further, the watermark image is scrambled using Arnold Map technique to avoid the correlation between image pixel. The proposed method provides a peak signal-to-noise ratio (PSNR) in the range of 35.57 dB to 36.80 dB and, a structural similarity index (SSIM) between 0.91 to 0.93 without attack for six sample datasets. It provides robustness for different attacks and offers SSIM in between 0.6 to 0.87 and normalized Correlation (NC) in between 0.8 to 0.91 which is superior over traditional techniques.