Pyramid transform and scale-space analysis in image analysis

Yoshihiko Mochizuki*, Atsushi Imiya

*この研究の対応する著者

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

The pyramid transform compresses images while preserving global features such as edges and segments. The pyramid transform is efficiently used in optical flow computation starting from planar images captured by pinhole camera systems, since the propagation of features from coarse sampling to fine sampling allows the computation of both large displacements in low-resolution images sampled by a coarse grid and small displacements in high-resolution images sampled by a fine grid. The image pyramid transform involves the resizing of an image by downsampling after convolution with the Gaussian kernel. Since the convolution with the Gaussian kernel for smoothing is derived as the solution of a linear diffusion equation, the pyramid transform is performed by applying a downsampling operation to the solution of the linear diffusion equation.

本文言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ページ78-109
ページ数32
7474 LNCS
DOI
出版ステータスPublished - 2012
イベント15th International Workshop on Theoretical Foundations of Computer Vision - Dagstuhl Castle
継続期間: 2011 6 262011 7 1

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7474 LNCS
ISSN(印刷版)03029743
ISSN(電子版)16113349

Other

Other15th International Workshop on Theoretical Foundations of Computer Vision
CityDagstuhl Castle
Period11/6/2611/7/1

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)
  • 理論的コンピュータサイエンス

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