Feature-preserving thumbnail generation based on graph cuts

Seong Gyun Jeong, Chang-Su Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A novel algorithm for thumbnail generation, which preserves characteristic features of a source image including blurs and textures, is proposed in this work. When a source image is subsampled to generate a thumbnail, important visible cues, such as blurs and noises, are lost. To overcome this drawback, we first create multiple thumbnail candidates that accentuate three classes of image features: focal blur, motion blur, and detail. Then, we obtain the final thumbnail by composing these candidates adaptively. Assuming that image features are spatially varying but locally static, we formulate the composition task as a labeling problem, and employ the graph-cut optimization technique to solve the problem. Simulation results demonstrate that the proposed algorithm provides feature-preserving thumbnails efficiently.

Original languageEnglish
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages1081-1084
Number of pages4
DOIs
Publication statusPublished - 2011
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: 2011 Sep 112011 Sep 14

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2011 18th IEEE International Conference on Image Processing, ICIP 2011
CountryBelgium
CityBrussels
Period11/9/1111/9/14

Keywords

  • Thumbnail generation
  • blur analysis
  • detail enhancement
  • graph cuts
  • image resampling

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Fingerprint Dive into the research topics of 'Feature-preserving thumbnail generation based on graph cuts'. Together they form a unique fingerprint.

Cite this