Using Hilbert curve in image storing and retrieving

  • Authors:

  • Zhexuan Song;Nick Roussopoulos

  • Affiliations:

  • Department of Computer Science, University of Maryland, College Park, MD;Department of Computer Science and Institute for Advanced Computer Studies, University of Maryland, College Park, MD

  • Venue:
  • Information Systems
  • Year:
  • 2002

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Abstract

In this paper, we propose a method to accelerate the speed of subset query on uncompressed images. First, we change the method to store images: the pixels of images are stored on the disk in the Hilbert order instead of row-wise order that is used in traditional methods. After studying the properties of the Hilbert curve, we give a new algorithm which greatly reduces the number of data segments in subset query range. Although, we have to retrieve more data than necessary, because the speed of sequential readings is much faster than the speed of random access readings, it takes about 10% less elapsed time in our algorithm than in the traditional algorithms to execute the subset queries. In some systems, the saving is as much as 90%.