Multiple description (MD) coding has been a popular choice for robust data transmission over the unreliable network channels. Lattice vector quantization provides lower computation for efficient data compression. In this paper, a new MD coinciding lattice vector quantizer (MDCLVQ) is presented. The design of the quantizer is based on coinciding 2-D hexagonal sublattices. The coinciding sublattices are geometrically similar sublattices, with the same index but generated by different generator matrices. A novel labeling algorithm based on the hexagonal coinciding sublattices is also developed. Performance results of the MDCLVQ scheme, together with the new labeling algorithm applied to standard test images, show improvements of the central and side decoders, as compared with the renowned techniques for several test images.
Secure communication of medical images is essential to telemedicine. Message Authentication Codes (MAC) can be embedded inside medical images to protect their integrity. Fragile watermarking algorithms are suitable options since they can be used to detect any tampering attempt. In this paper, a novel fragile data-hiding algorithm based on Integer-to-Integer Discrete Wavelet Transforms (IIDWT) and A 5 Lattice Vector Quantization (LVQ) is proposed. In the proposed data-hiding algorithm, a combination of the medical image Metadata and a MAC is embedded into the medical image. The Metadata includes information about the patient such as name, family, birthday, the place where it is created such as the name of the hospital, and the physician's name. To preserve the privacy of the patients and the physician/hospital, the Metadata is then replaced with fake information. The receiver can extract the Metadata and the MAC. If the extracted MAC is the same as the expected MAC, the integrity of the medical image is guaranteed. Otherwise, a tampering attempt is detected. The proposed algorithm can embed 50% more data than similar algorithms in medical images while keeping the Peak Signal to Noise Ratio (PSNR) in acceptable ranges. Furthermore, the proposed algorithm is applied to a dataset of medical images and high PSNR values above 53.88 dB are experienced.INDEX TERMS Data hiding, privacy, medical image privacy, fragile data hiding, integer discrete wavelet transforms, lattice vector quantization.
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