This paper introduces a new structure for stack lter-ing, where the lter adapts to the local characteristics encountered in data. Both supervised and unsupervised techniques for optimal design are investigated. We split the image into small regions and select the stack lter to process each region according to the spatial domain or threshold level domain characteristics of the input signal. This...

We present an intelligent night vision system for automobiles in this paper. This system, implemented mainly by adopting infrared cameras and computer vision techniques, aims at enhancing safety and convenience of night driving by providing functionalities such as adaptive night vision, road sign detection and recognition, scene zooming and spotlight projection. We have tested the system in bot...

In this article we develop convergence theory for a general class of adaptive approximation algorithms for abstract nonlinear operator equations on Banach spaces, and then use the theory to obtain convergence results for practical adaptive finite element methods (AFEM) applied to several classes of nonlinear elliptic equations. In the first part of the paper, we develop a weak-* convergence fra...

Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as biological movement systems. So far, due to sparsity of data in high dimensional spaces, learning in such settings requires a significant amount of prior knowledge about the learning task, usually provided by a human expert. In ...

Current schemes for texture compression fail to exploit spatial coherence in an adaptive manner due to the strict efficiency constraints imposed by GPU-based, fragment-level decompression. In this paper we present a texture compression framework for quasi-lossless, locally-adaptive compression of graphics data. Key elements include a Hilbert scan to maximize spatial coherence, efficient encodin...

a parallel algorithm for generating t-ary tree sequences in reverse b-order is presented. the algorithm generates t-ary trees by 0-1 sequences, and each 0-1 sequences is generated in constant average time o(1). the algorithm is executed on a crew sm simd model, and is adaptive and cost-optimal. prior to the discussion of the parallel algorithm a new sequential generation with o(1) average time ...

Image and audio data are examples of domains in which DPCM (Diierential Pulse Coded Modulation) is an eeective method for removing much of the linear correlation between data samples. However, most simple DPCM schemes cannot simultaneously cater for smooth signals, noisy signals, and discontinuities such as edges in images. To overcome this, many adaptive DPCM schemes have been proposed, includ...

We describe a hybrid meta-heuristic algorithm for combinatorial optimization problems with a specific reference to the travelling salesman problem (TSP). The method is a combination of a genetic algorithm (GA) and greedy randomized adaptive search procedure (GRASP). A new adaptive fuzzy a greedy search operator is developed for this hybrid method. Computational experiments using a wide range of...