-estimators of location is also established. Algorithms for two low-level vision tasks, discontinuity preserving smoothing and image segmentation are described as applications. In these algorithms the only user set parameter is the resolution of the analysis, and either gray level or color images are accepted as input

to signal delay estimation remote sensing. Under the two-dimensional (2-D) translational motion model, we further extend the pseudophase techniques to the DCT-based motion estimation (DXT-ME) algorithm for 2-D signals/images. The DXT-ME algorithm has certain advantages over the commonly used full search

in networked dynamic systems and diverse applications including synchronization of coupled oscillators, flocking, formation control, fast consensus in small-world networks, Markov processes and gossip-based algorithms, load balancing in networks, rendezvous in space, distributed sensor fusion in sensor

Compressed sensing is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper we present a theoretical analysis of the iterative hard thresholding algorithm when applied to the compressed sensing recovery

In this paper, we present a DCT-based data-hiding method robust to cropping. As it works in the DCT-domain, it is also robust to JPEG compression. A cropping operation on a JPEG image leads to the ap-plication of an additionnal compression. So, we achieve ro-bustness to several JPEG compressions

: We present the methods of improving the efficiency of Block DCT-based compression algorithm in the application to medical images archiving. The decrese of bit rate: for CR images up to 6%, for scintigraphy images up to 35%, for USG images up to 7% was achieved (in comparison to JPEG algorithm

. In the paper a new DCT-based shape-adaptive transform algorithm is presented. The transform is derived from the DCT algorithm flowgraph by substitution of operations in such a way that region and background samples are not mixed together. The computational complexity of the algorithm

A 2D DCT-based approach to compressing acoustic features for remote speech recognition applications is presented. The coding scheme involves computing a 2D DCT on blocks of feature vectors followed by uniform scalar quantization, run-length and Huffman coding. Digit recognition experiments were

define the target, system, environment, and fault models. Based on the performance requirements of the scenario and the sensing, communication, energy, and computation ability of the sensor network, we explore the design space of sensors, signal processing algorithms, communications, networking

In this paper we introduce a new compressed representation for the connectivity of a triangle mesh. We present local compression and decompression algorithms which are fast enough for real time applications. The achieved space compression rates keep pace with the best rates reported for any known