With pervasive applications of medical imaging in health-care, biomedical image segmentation plays a central role in quantitative analysis, clinical diagnosis, and medical intervention. Since manual annotation suffers limited reproducibility, arduous efforts, and excessive time, automatic segmentation is desired to process increasingly larger scale histopathological data. Recently, deep neural ...

The performance of distributed source coding methods based on scalar quantization followed by scalar entropy coding is investigated. For a fixed quantizer, the problem is converted to that of zero-error entropy coding for bipartite graphs with a special structure. It is then experimentally shown that for bipartite graphs corresponding to jointly Gaussian sources and high-resolution uniform quan...

Color quantization is the process of reducing the number of colors in a digital image. The main objective of quantization process is that significant information should be preserved while reducing the color of an image. In other words, quantization process shouldn’t cause significant information loss in the image. In this paper, a short review of color quantization is presented and a new color ...

Quantization effects are inevitable in networked control systems (NCSs). These quantization effects can be reduced by increasing the number of quantization levels. However, increasing the number of quantization levels may lead to network congestion, (i.e., the network needs to transfer more information than its capacity). In this paper, we investigate the problem of designing a robust H∞output ...

We review optimal quantization methods for numerically solving nonlinear problems in higher dimension associated with Markov processes. Quantization of a Markov process consists in a spatial discretization on finite grids optimally fitted to the dynamics of the process. Two quantization methods are proposed: the first one, called marginal quantization, relies on an optimal approximation of the ...

This paper introduces a Quantization-based System Modeling (QSM) which performs reduction of data traffic requirements in grid computing. The QSM is based on a quantization of system state and provides a high performance grid computing. For realization of QSM in grid computing, this paper introduces how to perform data transmission reduction using quantization approach and suggests the more eff...

Image retrieval based on color histograms requires quantization of a color space. Uniform scalar quantization of each color channel is a popular method for the reduction of histogram dimensionality. With this method, however, no spatial information among pixels is considered in constructing the histograms. Vector quantization (VQ) provides a simple and effective means for exploiting spatial inf...

A new class of image coding algorithms coupling standard scalar quantization of frequency coefficients with tree-structured quantization (related to spatial structures) has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical representation. This paper addresses the problem of how spatial quantization modes and standard scalar quanti...

It is known that the conductance of a quantum point contact is quantized in units of 2e2/h and this quantization is destroyed by a non-adiabatic scatterer in the point contact, due to backscattering. Recently, it was shown [Phys. Rev. Lett. 71, 137 (1993)] that taking many non-adiabatic scatterers periodically in a quantum channel, the quantization can be recovered. We study this conductance qu...

A uniied analysis of several polar quantization schemes is developed by focusing on their point densities and inertial prooles and using Bennett's integral to express the mean-squared error. The subsequent analysis is straightforward and leads to new insights into the relationship between polar quantization and Cartesian quantization. With this approach, unrestricted polar quantization, which i...