An efficient watermarking technique for satellite images using discrete cosine transform

Saeed AL-Mansoori

doi:10.1117/12.979185

24 October 2012 An efficient watermarking technique for satellite images using discrete cosine transform

Saeed AL-Mansoori

Proceedings Volume 8539, High-Performance Computing in Remote Sensing II; 85390A (2012) https://doi.org/10.1117/12.979185
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

Due to the significant progress in science and technology, the digital world became an interesting topic for many studies. “Data Security” is one of the main concepts related to the digital world especially in the field of remote sensing. Therefore, to deal with this matter the “Watermarking” concept was introduced. The idea of digital image watermarking is to embed the information within a signal (i.e. image, video, etc.), which cannot be easily extracted by a third party. This will generate a copyright protection and authentication for the owner(s). Emirates Institution for Advanced Science and Technology (EIAST) as an owner provides satellite images captured by DubaiSat-1 satellite to customers. The aim of this study is to implement a robust algorithm to hide EIAST logo within any delivered image in order to increase the data security and protect the ownership of DubaiSat-1 images. In addition, it is necessary to provide a high quality images to the end-user; nevertheless, adding any information (logo) to these images will affect its quality. Therefore, the model will be designed to keep the observable difference between the watermarked and original image at minimum. Moreover, the watermark should be difficult to remove or alter without the degradation of the host image. This study will be based on Discrete Cosine Transform (DCT) to provide an excellent and highly robust protection in cases such as noise addition, cropping, rotation and JPEG compression attacks.

Citation Download Citation

Saeed AL-Mansoori "An efficient watermarking technique for satellite images using discrete cosine transform", Proc. SPIE 8539, High-Performance Computing in Remote Sensing II, 85390A (24 October 2012); https://doi.org/10.1117/12.979185

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