Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Compressive Sensing: Single Pixel SWIR Imaging of Natural Scenes
Linköping University, Department of Electrical Engineering, Computer Vision.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Photos captured in the shortwave infrared (SWIR) spectrum are interesting in military applications because they are independent of what time of day the pic- ture is captured because the sun, moon, stars and night glow illuminate the earth with short-wave infrared radiation constantly. A major problem with today’s SWIR cameras is that they are very expensive to produce and hence not broadly available either within the military or to civilians. Using a relatively new tech- nology called compressive sensing (CS), enables a new type of camera with only a single pixel sensor in the sensor (a SPC). This new type of camera only needs a fraction of measurements relative to the number of pixels to be reconstructed and reduces the cost of a short-wave infrared camera with a factor of 20. The camera uses a micromirror array (DMD) to select which mirrors (pixels) to be measured in the scene, thus creating an underdetermined linear equation system that can be solved using the techniques described in CS to reconstruct the im- age. Given the new technology, it is in the Swedish Defence Research Agency (FOI) interest to evaluate the potential of a single pixel camera. With a SPC ar- chitecture developed by FOI, the goal of this thesis was to develop methods for sampling, reconstructing images and evaluating their quality. This thesis shows that structured random matrices and fast transforms have to be used to enable high resolution images and speed up the process of reconstructing images signifi- cantly. The evaluation of the images could be done with standard measurements associated with camera evaluation and showed that the camera can reproduce high resolution images with relative high image quality in daylight.

Place, publisher, year, edition, pages
2018. , p. 73
Keywords [en]
Compressed sensing, Compressive sensing, CS, Compressive imaging, compressed imaging, CI, SPC, Single pixel camera, single pixel imaging, SWIR, Short-wavelength infrared, IR, infrared, Natural Scenes, DMD, Digital micromirror device, FOI
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-145363ISRN: LiTH-ISY-EX--18/5108--SEOAI: oai:DiVA.org:liu-145363DiVA, id: diva2:1185507
Subject / course
Computer Vision Laboratory
Supervisors
Examiners
Available from: 2018-02-28 Created: 2018-02-25 Last updated: 2018-02-28Bibliographically approved

Open Access in DiVA

Compressive_Sensing_Single_Pixel_SWIR_Imaging_of_Natural_Scenes(21049 kB)98 downloads
File information
File name FULLTEXT01.pdfFile size 21049 kBChecksum SHA-512
92a5e7ae92c7f54074cbaa96a7bf30e32cefeae40bd8d8ea225f51a24e97206e79cb11578bf841e09ef366b4d1cb9692a8fda8e7a954876287b583b33e02d082
Type fulltextMimetype application/pdf

By organisation
Computer Vision
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 98 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 243 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf