In this article, an efficient vector quantization (VQ) scheme called side-match finite-state vector quantization with adaptive block classification is presented for image compression. It makes use of edge information contained in image in additional to the average values of blocks forming the image. In order to achieve low bit rate coding while preserving good quality images, neighboring blocks are utilized to predict the class of current block. Image blocks are mainly classified as edge blocks and non-edge blocks in this coding scheme. To improve the coding efficiency, edge blocks and non-edge blocks are further reclassified into different classes, respectively. Moreover, the number of bits for encoding an image is greatly reduced by foretelling the class of input block and applying small state codebook in corresponding class. The improvement of the proposed coding scheme is attractive as compared with other VQ techniques.

MPEG-4 emphasizes on coding efficiency and allows for content-based access and transmission of arbitrary shaped object. It addresses the encoding of video object using shape coding, motion estimation, and texture coding for interactivity, high compression ratio, and scalability. In this letter, an advanced object-adaptive vertex-based shape coding method is proposed for encoding the shape of video objects. This method exploits octant-based representation to represent the relation of adjacent vertices and that relation can be used to improve coding efficiency. Simulation results demonstrate that the proposed method may reduce more bits for closely spaced vertices.

A wavelet-based vector quantization scheme for image compression is introduced here. The proposed scheme obtains a better compression efficiency by the following three methods. (1) Utilizing the correlation among wavelet coefficients. (2) Placing different emphasis on wavelet coefficients at different levels. (3) Preserving the most important information of the image. In our experiments, simulation results show that this technique outperforms the recent SMVQ-ABC [1] and WTC-NIVQ [2] techniques.

An adaptive data hiding scheme capable of hiding considerable quantities of secret data while preserving acceptable visual quality for cover images is proposed. The major idea of this scheme is to hide secret data into the compressed codes of cover image during the encoding process of side-match vector quantization (SMVQ) such that the interceptors will not capture the secret information. Based on the experimental results, it is confirmed that the proposed scheme is better than earlier works. Moreover, the receiver can efficiently receive both the compressed cover image and the hidden secret data at the same time.

A secret image transmission scheme based on vector quantization (VQ) and a secret codebook is proposed in this article. The goal of this scheme is to transmit a set of good-quality images secretly via another high-quality cover image with the same image size. In order to reduce the data size of secret images, the images are encoded by an adaptive codebook. To guarantee the visual quality of secret images, the adaptive codebook applied at the transmitter is transmitted to the receiver secretly as well. Moreover, to enhance the security of the proposed scheme and to compact the data size of the codebook, the adaptive codebook is encoded based on VQ using another codebook generated from the cover image. Experiments show impressive results.