• DocumentCode
    1765748
  • Title

    Multiresolution Imaging

  • Author

    Xiaoqiang Lu ; Xuelong Li

  • Author_Institution
    Center for Opt. IMagery Anal. & Learning (OPTIMAL), Xi´an Inst. of Opt. & Precision Mech., Xi´an, China
  • Volume
    44
  • Issue
    1
  • fYear
    2014
  • fDate
    Jan. 2014
  • Firstpage
    149
  • Lastpage
    160
  • Abstract
    Imaging resolution has been standing as a core parameter in various applications of vision. Mostly, high resolutions are desirable or essential for many applications, e.g., in most remote sensing systems, and therefore much has been done to achieve a higher resolution of an image based on one or a series of images of relatively lower resolutions. On the other hand, lower resolutions are also preferred in some cases, e.g., for displaying images in a very small screen or interface. Accordingly, algorithms for image upsampling or downsampling have also been proposed. In the above algorithms, the downsampled or upsampled (super-resolution) versions of the original image are often taken as test images to evaluate the performance of the algorithms. However, there is one important question left unanswered: whether the downsampled or upsampled versions of the original image can represent the low-resolution or high-resolution real images from a camera? To tackle this point, the following works are carried out: 1) a multiresolution camera is designed to simultaneously capture images in three different resolutions; 2) at a given resolution (i.e., image size), the relationship between a pair of images is studied, one gained via either downsampling or super-resolution, and the other is directly captured at this given resolution by an imaging device; and 3) the performance of the algorithms of super-resolution and image downsampling is evaluated by using the given image pairs. The key reason why we can effectively tackle the aforementioned issues is that the designed multiresolution imaging camera can provide us with real images of different resolutions, which builds a solid foundation for evaluating various algorithms and analyzing the images with different resolutions, which is very important for vision.
  • Keywords
    cameras; computer vision; image capture; image resolution; computer vision; image capture; image downsampling; image upsampling; multiresolution camera; multiresolution imaging; Cameras; Lighting; Optical imaging; Sensors; Spatial resolution; Multiresolution camera; downsampling; multiresolution imaging; optimal imagery; super-resolution;
  • fLanguage
    English
  • Journal_Title
    Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    2168-2267
  • Type

    jour

  • DOI
    10.1109/TCYB.2013.2286496
  • Filename
    6671369