The important point about VQ is that, we require reproduction vectors (instead of reproduction levels) that are known by the encpder and the decoder. The encoder takes an input vector, determines the best representing reproduction vector, and transmits the index of that vector. The decoder takes that index, and forms the reproduction vector because it already knows the reproduction vectors inst...

In this paper, a reversible data-hiding scheme in encrypted, vector quantization (VQ) encoded images is proposed. During image encryption, VQ-encoded image, including codebook and index table, encrypted by content owner with stream-cipher permutation to protect the privacy of contents. As for additional-data embedding, baseline method first proposed its corresponding optimized then given. By gr...

Natural images can be segmented into regions with widely varying perceptual importance. There are three types of regions in a typical image. The region in which the contrast between objects and background is high is categorized as the edge. Due to the high contrast, human eyes will naturally pay much attention to the edges. Thus, edge regions are very important for human perception. The second ...

Signal compression is essential for applications which require the minimization of the storage and/or transmission requirements, such as multimedia communications, integrated services digital networks (ISDN), web browsing, voice response systems, cellular telephony, storage of medical images, archiving of fingerprints, and transmission of remote sensing images obtained from satellites. Vector q...

Vector quantization (VQ) can be used to compress images with high compression ratios. The VQ methods produce a sequence of code values which identifies the codebook model vectors to be used as blocks of pixels in the decoded image. In this paper we define a novel non-lossy and computationally efficient method to further compress the code sequence based on the relative frequencies of the code va...

Compression of a noisy source is usually a two stage problem, involving the operations of estimation (denoising) and quantization. A survey of literature on this problem reveals that for the squared error distortion measure, the best possible compression strategy is to subject the noisy source to an optimal estimator followed by an optimal quantizer for the estimate. What we present in this pap...

In this paper, a new digital watermarking method based on vector quantization (VQ) is proposed. In contrast with conventional VQ-based watermarking schemes, the mean of sub-blocks is used to train the VQ codebook. In addition, the Anti-Gray Coding (AGC) technique is employed to enhance the robustness of the proposed watermarking scheme. In this scheme, the secret keys are used to hide the assoc...

A modified integral counting method (MICM) with various quenched samples (MICM-VQ) has been investigated for its applicability for different scintillators using b emitters, C and S. To assess the influence of scintillators, three sets of C quenched standards and two S cocktail series were prepared. Two sets of C quenched standards were used for the toluene-compatible scintillator, the other for...

Key Laboratory of Quantum Information, University of Science and Technology of China, Chinese Academy of Sciences, Hefei, Anhui 230026, China College of Mathematics and Software Science, Sichuan Normal University, Chengdu, Sichuan 610066, People’s Republic of China Abstract Many classical encoding algorithms of Vector Quantization (VQ) of image compression that can obtain global optimal solutio...

This paper describes an eeort to extend the Lempel-Ziv algorithm to a practical universal lossy compression algorithm. It is based on the idea of approximate string matching with a rate-distortion (R ? D) criterion, and is addressed within the framework of vector quantiza-tion (VQ) 4]. A practical one pass algorithm for VQ codebook construction and adaptation for individual signals is developed...