Real-Time Memory-Adaptive Image Compression for Resource-Constrained Systems

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• Adam Powell (Imperial College)
• Tuesday 14 June 2011, 10:00-11:00
• Level 9 Mahanakorn Lab., EE Dept..

If you have a question about this talk, please contact Grigorios Mingas.

Current image compression techniques, despite being widespread, contain a number of assumptions that make them ill-suited for certain applications. One of these assumptions generates problems in memory-constrained situations. More specifically, the output generated by a compression algorithm does not have to deal with changing memory constraints _after_ it has been encoded. This talk examines the use of Principal Component Analysis (PCA) as a method for real-time memory-adaptive image compression. The aim of this system is to explore the trade-off of memory usage and quality of the output when the amount of data to be processed is unknown. To adapt to changing memory conditions, the system must have a method to efficiently reduce the amount of memory it takes to store a given image and do this in an on-line fashion. By freeing memory as limits are reached, it allows for a graceful degradation of quality over time while still maintaining useful output.

This talk is part of the CAS Talks series.

This talk is included in these lists:

• Andrea Picciau's list
• CAS Talks
• Circuits and Systems Group: Internal Seminars
• Level 9 Mahanakorn Lab., EE Dept.

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