In this paper, a novel greyscale image coding technique based on vector quantization (VQ) is proposed. In VQ, the recon− structed image quality is restricted by the codebook used in the image encoding/decoding procedures. To provide a better image quality using a fixed−sized codebook, the codebook expansion technique is introduced in the proposed technique. In addition, the block prediction tec...

Image retrieval and image compression are each areas that have received considerable attention in the past. In this work, we present an approach for content-based image retrieval (CBIR) using vector quantization (VQ). Using VQ allows us to retain the image database in compressed form without any need to store additional features for image retrieval. The hope is that encoding an image with a cod...

Develops a technique for improving the applicability of complete, nonorthogonal, multiresolution transforms to image coding. As is well known, the L(2) norm of the quantization errors is not preserved by nonorthogonal transforms, so the L(2) reconstruction error may be unacceptably large. However, given the quantizers and synthesis filters, the authors show that this artifact can be eliminated ...

This paper describes an approach that performs spike sorting by a nonparametric density estimation technique under a Bayesian framework. The technique is based on an optimal quantization method. We performed experiments on simulated and real spike signals. The results are comparable with what is reported in the literature.

Perturbed Quantization (PQ) steganography scheme is almost undetectable with the current steganalysis methods. We present a new steganalysis method for detection of this data hiding algorithm. We show that the PQ method distorts the dependencies of DCT coefficient values; especially changes much lower than significant bit planes. For steganalysis of PQ, we propose features extraction from the e...

For constructing the best local codebook for image compression, there are many Vector Quantization (VQ) procedures, but simplest VQ procedure is Linde–Buzo–Gray (LBG) procedure. Techniques such as Gaussian Dissemination Function (GDF) used searching process in generating a global particle swarm optimization (PSO), Honeybee mating (HBMO), and Firefly (FA) procedures. However, when velocity very ...

Many image compression techniques require the quantization of multiple vector sources with significantly different distributions. With vector quantization (VQ), these sources are optimally quantized using separate codebooks, which may collectively require an enormous memory space. Since storage is limited in most applications, a convenient way to gracefully trade between performance and storage...

Multiple description (MD) coding has evolved as a promising technique for promoting error resiliency of multimedia system in real-time application programs over error-prone communicational channels. Although multiple description lattice vector quantization (MDCLVQ) is an efficient method for transmitting reliable data in the context of potential error channels, this method doesn’t consider disc...