Image coding with vector quantization (VQ) reveals several defects which include edge degradation and high encoding complexity. This paper presents an edge-preserving coding system based on VQ to overcome these defects. A signal processing unit first classifies image blocks into low-activity or high-activity class. A high-activity block is then decomposed into a smoothing factor, a bit-plane an...

This paper proposes a reversible data embedding scheme based on a VQ image compression technique which emphasizes that the original VQ compressed codes can be recovered after data extraction. In this proposed scheme, a VQ codebook, which had already been clustered into three groups, was adopted to achieve secret concealment and data recovery. In order to embed more secret data, the concepts of ...

Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor, and available experimental and routine therapies result in limited survival benefits. A vulnerability of GBM cells to catastrophic vacuolization and cell death, a process termed methuosis, induced by Vacquinol-1 (VQ-1) has been described earlier. In the present study, we investigate the efficacy of VQ-1 treatment in...

Data hiding is a form of steganography to embed secret data into digital media for the purpose of content authentication, annotation and copyright protection. Lossless data hiding is a special kind of data hiding technique that guarantees the digital media can be losslessly restored after the secret data are correctly extracted. In the past several years, several reversible data hiding schemes ...

A novel image compression algorithm based on vector quantization (VQ) technique is proposed in this paper. Adaptive resolution VQ (AR-VQ) method, which is composed of three key techniques, i.e., the edge detection, the resolution conversion, and the block alteration, can realize much superior compression performance than the JPEG and the JPEG-2000. On the compression of the XGA (1024x768 pixels...

Vector Quantization (VQ) is a powerful techreported in the literature. One class of architectures is nique for low-bit rate image and video compression. However, VQ is a computational intensive technique. In this paper, a Computational RAM (C*RAM) implementation of VQ for real-time image compression is presented. The C*RAM architecture enables parallel search in the direction of codewords. The ...

To enhance the traditional vector quantisation (VQ) system by adding the watermarking ability, a digital image watermarking scheme, which modifies the VQ indices to carry watermark bits, is presented. This scheme partitions the main codebook into two subcodebooks by referring to the user-key. Then, for each input vector of the cover image, a subcodebook is selected according to the watermark bi...

Vector quantization (VQ) is a efficient technique for data compression with a minimum distortion. VQ is widely used in applications as speech and image coding, speech recognition, and image retrieval. This paper presents a novel fast nearestneighbor algorithm and shows its application to speech recognition. The proposed algorithm is based on a fast preselection that reduces the search to a limi...

The idea of applying vector quantization (VQ) to linear prediction coding (LPC) to realize a very low bit-rate speech coder with reasonable speech quality is investigated in this research. Instead of encoding LPC parameters directly, line spectral frequency (LSF) coefficients are obtained through a transformation of LPC and then encoded via VQ in the proposed scheme. In order to utilize the int...

In cases of extremely imbalanced dataset with high dimensions, standard machine learning techniques tend to be overwhelmed by the large classes. This paper rebalances skewed datasets by compressing the majority class. This approach combines Vector Quantization and Support Vector Machine and constructs a new approach, VQ-SVM, to rebalance datasets without significant information loss. Some issue...