GPU-specific reformulations of image compression algorithms

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Authors

MATELA Jiří HOLUB Petr JIRMAN Martin ŠROM Martin

Year of publication 2012
Type Article in Proceedings
Conference Proceedings of Applications of Digital Image Processing XXXV
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1117/12.929971
Field Informatics
Keywords GPU; parallel; reformulation; JPEG; JPEG2000; Context Modeling; Arithmetic coding; MQ-Coder; Huffman coding
Description Image compressions have a number of applications in various fields where the processing throughput and/or latency is a crucial attribute and the main limitation with state of the art implementations of compression algorithms. At the same time the contemporary GPUs provide a tremendous processing power applicable to the image compression acceleration but it calls for a specific algorithm design. We discuss the key components of successful GPU algorithm design and demonstrate this on JPEG2000 compression chain, which contains several types of algorithms: from DWT which is inherently well suited to GPU, through context modeling requiring reformulation in order to perform well on GPU, to arithmetic coding which does not fit the paradigm well but can be optimized to perform faster than CPU versions. Performance evaluation of the optimized JPEG2000 chain will be used to demonstrate the importance of various aspects of GPU programming, especially with respect to real-time applications.
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