Paper
24 August 2010 Watermarking scheme for tampering detection in remote sensing images using variable size tiling and DWT
Jordi Serra-Ruiz, David Megías
Author Affiliations +
Abstract
In this paper, a semi-fragile watermarking scheme specifically developed for remote sensing images is presented. The method can be tuned to embed the mark depending on the content and the signature to be protected. The suggested method is based on tiling the original three-dimensional images into blocks of different sizes according to the relevance of the area to protect (bigger blocks are used for less relevant areas). For each of these blocks, the discrete Wavelet transform (DWT) is applied to each selected spectral band and the obtained LL DWT sub-bands are used to build a Tree-Structured Vector Quantization tree. This tree is then modified using an iterative algorithm until it satisfies some criterion. Once the target value is reached, the marked block is obtained using the new LL DWT sub-band together with the other original sub-bands (LH, HL and HH) of the block. A secret key produces a different criterion for each block in order to avoid copy-and-replace attacks. The use of the LL DWT sub-band for each spectral band makes it possible to obtain robustness against near-lossless compression attacks and, at the same time, relatively strong modifications are detected as tampering.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jordi Serra-Ruiz and David Megías "Watermarking scheme for tampering detection in remote sensing images using variable size tiling and DWT", Proc. SPIE 7810, Satellite Data Compression, Communications, and Processing VI, 78100A (24 August 2010); https://doi.org/10.1117/12.860573
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Digital watermarking

Discrete wavelet transforms

Image processing

Remote sensing

Image compression

Hyperspectral imaging

Image segmentation

Back to Top