A RLS Based PCA for Compressing Relighting Data Sets(Image/Visual Signal Processing)(<Special Section>Digital Signal Processing)

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概要

• 論文の詳細を見る

• In image-based relighting (IBR), users are allowed to control the illumination condition of a scene or an object. A relighting data set (RDS) contains a large number of reference images captured under various directional light sources. This paper proposes a principal component analysis (PCA) based compression scheme that effectively reduces the data volume. Since the size of images is very large, a tiling recursive least square PCA (RLS-PCA) is used. The output of RLS-PCA is a set of eigenimages and the corresponding eigen coefficients. To further compress the data, extracted eigenimages are compressed using transform coding while extracted eigen coefficients are compressed using uniform quantization with entropy coding. Our simulation shows that the proposed approach is superior to compressing reference images with JPEG and MPEG2.

• 社団法人電子情報通信学会の論文
• 2004-08-01

著者

• Wong Tien-tsin

  The Department Of Computer Science And Engineering The Chinese University Of Hong Kong

• Wang Z

  The Dept. Of Bme Shanghai Jiao Tong University

• Leung Chi-sing

  The Department Of Electronic Engineering City University Of Hong Kong

• HO Gary

  the Department of Electronic Engineering, City University of Hong Kong

• CHOY Kwok-Hung

  the Department of Electronic Engineering, City University of Hong Kong

• WANG Ze

  the Dept. of BME, Shanghai Jiao Tong University

• Ho Gary

  The Department Of Electronic Engineering City University Of Hong Kong

• Choy Kwok-hung

  The Department Of Electronic Engineering City University Of Hong Kong

関連論文

• A RLS Based PCA for Compressing Relighting Data Sets(Image/Visual Signal Processing)(Digital Signal Processing)

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