Using Quadtrees to Smooth Images

Abstract

Three methods for smoothing images are presented. All three use variable numbers of picture points over which the smoothing functions are defined. The first method examines the histogram of a neighborhood of each point. The subset of gray values most similar to that of the point is used in calculating the smoothing functions. The other two methods use quadtree approximations to smooth the image. One of these uses the sizes of the leaves in the quadtree to determine neighborhood sizes over which to apply a smoothing function, while the other refines the gross smoothing defined by the quadtree. All the methods perform fairly well, but the quadtree methods are particularly attractive because of the information about region sizes and homogeneity provided by the quadtree structure.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1980
Accession Number
ADA090247

Entities

People

  • Michael Shneier
  • Sanjay Ranade

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Applied Computer Science
  • Artificial Intelligence
  • Computer Science
  • Computer Vision
  • Computers
  • Computing-Related Activities
  • Digital Images
  • Frequency
  • Histograms
  • Homogeneity
  • Image Processing
  • Image Segmentation
  • Images
  • Maryland
  • Night Vision
  • Preprocessing
  • Universities

Fields of Study

  • Mathematics

Readers

  • Computer Vision.