We propose a novel, interactive content-aware zooming operator that allows effective and efficient visualization of high resolution images on small screens, which may have different aspect ratios compared to the input images. Our approach applies an image retargeting method in order to fit an entire image into the limited screen space. This can provide global, but approximate views for lower zo...

This paper is concerned with the stability analysis of networked control systems with dynamic quantization, variable sampling intervals and communication delays. A time-triggered zooming algorithm for the dynamic quantization at the sensor side is proposed that leads to an exponentially stable closed-loop system. The algorithm includes proper initialization of the zoomparameter.More precisely, ...

In this paper we address the problem of producing an enlarged picture from a given digital image. We propose a zooming technique based on ENO and WENO schemes that are high order accurate finite difference schemes designed for problems with piecewise smooth solutions containing discontinuities. ENO and WENO schemes have been quite successful in applications, especially for problems containing b...

A single sensor provided with a color filter array (CFA) format looks like a mosaic image. Each pixel in the image contains a primary color, red, green and blue, arranged alternately. Most previous interpolation and zooming techniques for CFA image utilize the gradient and the spatial information of the neighborhood color pixels around the interpolation positions. However, their characteristics...

in this article, we propose an adaptive grid based on mesh equidistribution principle for two-parameter convection-diffusion boundary value problems with continuous and discontinuous data. a numerical algorithm based on an upwind finite difference operator and an appropriate adaptive grid is constructed. truncation errors are derived for both continuous and discontinuous problems. parameter uni...

Locally Linear Embedding (LLE) algorithm is the first classic nonlinear manifold learning algorithm based on the local structure information about the data set, which aims at finding the low-dimension intrinsic structure lie in high dimensional data space for the purpose of dimensionality reduction. One deficiency appeared in this algorithm is that it requires users to give a free parameter k w...

An error-correcting code is said to be locally decodable if a randomized algorithm can recover any single bit of a message by reading only a small number of symbols of a possibly corrupted encoding of the message. Katz and Trevisan (On the efficiency of local decoding procedures for error correcting codes, STOC 2000, 80–86) showed that any such code C : {0, 1}n → Σ with a decoding algorithm tha...

We develop honest and locally adaptive confidence bands for probability densities. They provide substantially improved confidence statements in case of inhomogeneous smoothness, and are easily implemented and visualized. The article contributes conceptual work on locally adaptive inference as a straightforward modification of the global setting imposes severe obstacles for statistical purposes....

A data compression scheme that exploits locality of reference, such as occurs when words are used frequently over short intervals and then fall into long periods of disuse, is described. The scheme is based on a simple heuristic for self-organizing sequential search and on variable-length encodings of integers. We prove that it never performs much worse than Huffman coding and can perform subst...