| EPSRC Reference: |
EP/J020567/1 |
| Title: |
Algorithms for Data Simplicity |
| Principal Investigator: |
Tanner, Professor J |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Sch of Mathematics |
| Organisation: |
University of Edinburgh |
| Scheme: |
Standard Research |
| Starts: |
30 May 2012 |
Ends: |
31 August 2012 |
Value (£): |
39,695
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| EPSRC Research Topic Classifications: |
| Digital Signal Processing |
Image & Vision Computing |
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| EPSRC Industrial Sector Classifications: |
| Aerospace, Defence and Marine |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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09 Feb 2012
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Data Intensive Systems (DaISy)
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Announced
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Summary on Grant Application Form |
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Most of the information we encounter on a day to day basis has some inherent simplicity, from music having a limited number of dominant frequencies at any given time and natural images being composed of smooth regions separated by relatively few abrupt edges. This inherent simplicity can be leveraged to allow extraction of meaningful information from the vast data and for more efficient information acquisition. For example, consider consumer grade mega-pixel digital cameras. The camera has a carefully constructed array of millions of photodiodes, but as soon as the image is taken the camera compresses the data to a much smaller JPG format. This compression is crucial to allow for efficient storage and transmission of the image, but it is wasteful to have acquired millions of pixels and then to immediately compress and remove the measured image. Compressed sensing and matrix completion are techniques by which the camera can measure the image at a rate proportional to the size of the final compressed image, dramatically increasing the efficiency of the camera. Taking advantage of this technology requires the design of computationally efficient algorithms for the recovery of the image from the compressed measurements. This proposal concerns the design, analysis, and application of fast algorithms able to act on large data sets.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.ed.ac.uk |