Moad Med Sayah, Zermi Narima, Khaldi Amine, Kafi Med Redouane
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引用次数: 0
Abstract
How to guarantee the confidentiality of sensitive data communicated over the Internet and restrict access to designated information is today’s key security and protection concern in telemedicine. In this work, we suggest a reliable and blind medical image watermarking method that combines integer wavelet transform (IWT) and singular value decomposition to keep such information private. A major drawback of current IWT-based watermarking systems is their low embedding capacity. This paper suggests an IWT-based secure large capacity watermarking solution to overcome this specific drawback. The proposed technique effectively preserves a considerable quality of watermarked images, and the watermark is resistant to the most frequently used attacks in watermarking, according to experiment results on imperceptibility and robustness.
期刊介绍:
Rapid developments in the analog and digital processing of signals for communication, control, and computer systems have made the theory of electrical circuits and signal processing a burgeoning area of research and design. The aim of Circuits, Systems, and Signal Processing (CSSP) is to help meet the needs of outlets for significant research papers and state-of-the-art review articles in the area.
The scope of the journal is broad, ranging from mathematical foundations to practical engineering design. It encompasses, but is not limited to, such topics as linear and nonlinear networks, distributed circuits and systems, multi-dimensional signals and systems, analog filters and signal processing, digital filters and signal processing, statistical signal processing, multimedia, computer aided design, graph theory, neural systems, communication circuits and systems, and VLSI signal processing.
The Editorial Board is international, and papers are welcome from throughout the world. The journal is devoted primarily to research papers, but survey, expository, and tutorial papers are also published.
Circuits, Systems, and Signal Processing (CSSP) is published twelve times annually.