In this paper we propose a new observations selection technique in Vector Quantization context. The main idea is to select observations that are not representatives of their classes. The cells generated by the Vector Quantization are divided in regions of rejection. A number of controlled experiments were performed demonstrating the proposed methodology potentiality. Key-Words: Observations Sel...

This paper describes a technique to compress images based on vector quantization. The vector quantizer is designed to reduce both perceptual irrelevancy and mathematical redundancy. This is done without using transforms and entropic coding, which are normally used respectively prior and after quantization. Because of its structure, the vector quantizer can be implemented efficiently as a unifor...

Vector quantization is a powerful tool for speech coding applications. This paper deals with LPC Coding of speech signals which uses a new technique called Multi Switched Split Vector Quantization (MSSVQ), which is a hybrid of Multi, switched, split vector quantization techniques. The spectral distortion performance, computational complexity, and memory requirements of MSSVQ are compared to spl...

This paper introduces an efficient technique for pitch contour quantization designed mainly for applications that require storage of speech or prosodic information at a high compression ratio. Instead of quantizing the estimated pitch values directly, the proposed technique forms and quantizes a simplified model of the pitch contour. The simplified contour is constructed in such a manner that t...

This paper presents an error shaping technique for line spectrum frequency (LSF) vector quantization. The error shaping technique based on the weighted logarithm spectral distortion (WLSD) measure can be used for shaping the spectral distortion distribution ofquantization error into anydifferent curve depending on what kind of weighting function is used. However, the high computational complexi...

A new variable-rate embedded quantization technique, called Embedded Entropy-Constrained Trellis Coded Quantization (E-ECTCQ) is developed. Its performance is compared to that of variable-rate embedded scalar quantizers. Simulations indicate that performance depends both upon the number of embedded quantization stages and the number of trellis states.

In this paper we propose a new transform domain coding technique called transform trellis coded quantization (TTCQ) that is based on the trellis coded quantization technique recently proposed where Ungerboeck’s amplitude modulation trellises and set partitioning ideas are used for source coding. We combine the proposed technique with a transform domain formulation for small frame sizes obtainin...

An effective data reduction technique based on vector quantization is introduced for nonparametric classifier design. ” b o uew nonparametric classifiers are developed, and their performance is evaluated using various examples. The new methods maintain a classification accuracy that is competitive with that of classical methods but, at the same time, yields very high data reduction rates.

In this paper, we propose digital image watermarking algorithm in the multiwavelet transform domain. The embedding technique is based on the quantization index modulation technique and this technique does not require the original image in the watermark extraction. We have developed an optimization technique using the genetic algorithms to search for optimal quantization steps to improve the qua...

Data hiding is mainly used to hide the secret data into a cover data like a video file, an audio file, an image, etc. It is popularly used in medical and military applications. Nowadays reversible data hiding is the latest research area in the field of secret data hiding techniques. This paper covers many hiding and compression techniques like vector quantization (VQ), side match vector quantiz...