Geometric Super-resolution using Negative Rect Mask

In an electronic imaging system, image is retrieved using a Charged Coupled Device (CCD). Its finite pixel size integrates the optical information and limits the spatial resolution, whereas pixel-pitch provides the sampling interval. Spatial resolution can be improved if pixels of smaller sizes are...

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Bibliographic Details
Published inOptik (Stuttgart) Vol. 168; pp. 323 - 341
Main Authors Haq, Ihtsham ul, Mudassar, Asloob A.
Format Journal Article
LanguageEnglish
Published Elsevier GmbH 01.09.2018
Subjects
CCD-pixel
Computational decoding
Geometric superresolution
Mask scanning
Optical coding
Optical image processing
Spatial resolution
Subpixel
Optical coding
Computational decoding
Subpixel
Optical image processing
CCD-pixel
Mask scanning
Geometric superresolution
Spatial resolution
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ISSN0030-4026
1618-1336
DOI10.1016/j.ijleo.2018.04.033

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Summary:In an electronic imaging system, image is retrieved using a Charged Coupled Device (CCD). Its finite pixel size integrates the optical information and limits the spatial resolution, whereas pixel-pitch provides the sampling interval. Spatial resolution can be improved if pixels of smaller sizes are used or equivalently if Geometric Super-Resolution technique is achieved. In this paper, we are reporting use of the Negative rect mask (NRM) at image plane to achieve Geometric Super-resolution through sub-pixeling. The NRM is scanned over CCD in sub-pixel steps and image data is gathered. The target is assumed to be static during the scanning process. The data collected through CCD with NRM coding and the position information of the scanning mask provides a mean to render the geometrically super resolved image. The work is demonstrated in one and two dimensions with computer simulation. The results are also applicable on CMOS based imaging.
ISSN:0030-4026
1618-1336
DOI:10.1016/j.ijleo.2018.04.033