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                            Funding & Awards
 DeGrade It
Note:
              This awardee has received supplemental funding. This award detail page includes information about both the original award and supplemental awards.
Award Information
Awardee
              Trustees of Dartmouth College
Award #
              2016-R2-CX-0012
Funding Category
              Continuation
Location
                    Hanover, NH
Awardee County
              Grafton
Congressional District
              2
Status
              Closed
Funding First Awarded
              2016
Total funding (to date)
              $97,379
Original Solicitation
              NIJ FY 16 Graduate Research Fellowship in Science, Technology, Engineering, and Mathematics
Description of original award (Fiscal Year 2016, $47,868)
As submitted by the proposer: Extremely low-quality images  on the order of 10 to 20 pixels in size  appear with frustrating frequency in many investigations. Even the most advanced de-noising and super-resolution technologies are unable to extract useful information from such low-quality images. However, useful information is present in such highly degraded images. We propose that the way to extract this information is not to enhance an image, but to degrade an image. In particular we propose a new forensic approach that searches the space of possible content that when degraded matches the content of the low-quality image in question. Such an approach is particularly well suited to deciphering the identity of a license plate or the identity of individual in an extremely low-quality image or video.
Note:  This project contains a research and/or development component, as defined in applicable law.
ca/ncf
Supplemental Award 1 (Fiscal Year 2017, $49,511)
As submitted by the proposer: Extremely low-quality images  on the order of 10 to 20 pixels in size  appear with frustrating frequency in many investigations. Even the most advanced de-noising and super-resolution technologies are unable to extract useful information from such low-quality images.
However, useful information is present in such highly degraded images. We propose that the way to extract this information is not to enhance an image, but to degrade an image. In particular the researcher proposes a new forensic approach that searches the space of possible content that when degraded matches the content of the low-quality image in question. Such an approach is particularly well suited to deciphering the identity of a license plate or the identity of individual in an extremely low-quality image or video.
This project contains a research and/or development component, as defined in the applicable law, and complies with Part 200 Uniform Requirements  2 CFR 200.210(a) (14). nca/ncf


  
Grant-Funded Publications
        
                      Deciphering Severely Degraded License Plates

  
Date Created: July 19, 2016
    
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