Image compression helps in storing the transmitted data in proficient way by decreasing its redundancy. This technique helps in transferring more digital or multimedia data over internet as it increases the storage space. It is important to maintain the image quality even if it is compressed to certain extent. Depends upon this the image compression is classified into two categories: lossy and ...

This paper is devoted to the study of optimal image quantization and its sensitivity to initial conditions. The optimal mean squared algorithm is elaborated, for gray-level as well as for color images. A genetic quantization algorithm is developed, which is a hybrid technique combining optimal quantization with a genetic algorithm. It is shown that the latter technique is almost insensitive to ...

This report presents some results and findings of our work on very-lowbit-rate video compression systems using vector quantization (VQ). We have identified multiscale segmentation and variable-rate coding as two important concepts whose effective use can lead to superior compression performance. Two VQ algorithms that attempt to use these two aspects are presented: one based on residual vector ...

Quantization is a widely used technique in signal processing. The purpose of many quantization schemes is to faithfully reproduce the input signals. However, in many situations, one is more interested in comparison of different classes of signals in order to classify them into different categories. The classification criterion is based on comparing distances under certain metric. For classical ...

Figure 12: a) High-level block diagram of the segmented quantizer; b) quantization block details; c) signal processing model .. Figure 16: Estimated power spectra of a) the quantization noise sequences, and b) the running sums of the quantization noise sequences of the first-order ∆Σ modulator and the segmented quantizer presented in Section IV before and Ian Galton supervised the research whic...

Grouping algorithms based on histograms over measured image features have very successfully been applied to textured image segmentation [2, 11, 6]. However, the competing goals of statistical estimation significance demanding few quantization levels versus the necessary richness in representation often prevent a successful application for the color cue, since quantization may result in contouri...

Despite their widespread adoption, Product Quantization techniques were recently shown to be inferior to other hashing techniques. In this work, we present an improved Deep Product Quantization (DPQ) technique that leads to more accurate retrieval and classification than the latest state of the art methods, while having similar computational complexity and memory footprint as the Product Quanti...

This paper proposes some fast and simple quantization techniques to display.The main reason for adopting different techniques in vector quantizers VQ is to design an optimal quantizer. Since the actual probability distributions of image.Abstract: Image Compression is a technique for competently coding digital. Vector Quantization VQ is a block-coding technique that quantizes blocks of data.Defi...