A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimization principles and application performance evaluation of a multithreaded GPU using CUDA
Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming
High performance scalable image compression with EBCOT
IEEE Transactions on Image Processing
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In this paper, we explore the key factors in the design and implementation of visual computing (image processing and computer vision) algorithms on the massive parallel GPU (graphics processing units). The goal of the exploration is to provide common perspective and guidelines of using GPU for visual computing applications. We have selected three nontrivial applications (multiview stereo matching, linear feature extraction, and JPEG2000 image encoding) for the benchmarks, which show different characteristics in GPU parallel computing. Intensive analysis is performed to evaluate the characteristic of each algorithm and its effect on the performance. Based on this, we draw general guidelines of using GPU for the visual computing algorithms.