Presentation 2013-02-19
Region Adaptive Blind PSNR Estimation based on Spatial Frequency Characteristics
Takahiro KUMEKAWA, Jiro KATTO, Naofumi WADA,
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Abstract(in English) PSNR needs original pictures, but this is difficult for CGM contents like YouTube. Therefore, we had developed a blind PSNR estimation method in which multiple SVMs are prepared to learn differently encoded images in PSNR. We also tried a method which divides a frame into two regions by using. Saliency Map to estimate PSNR per region. However, this approach sometimes fails because it always tries to extract salient regions in a relative manner even if images are totally flat. Therefore, in this paper, we consider a method which uses AC levels of local small regions to separate input images instead of Saliency Map. Then, we confirm our method provides more stable results even when the previous method fails.
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Keyword(in English) Blind PSNR Estimation / Saliency Map / AC levels / SVM
Paper # ITS2012-55,IE2012-135
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Conference Information
Committee IE
Conference Date 2013/2/11(1days)
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Paper Information
Registration To Image Engineering (IE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Region Adaptive Blind PSNR Estimation based on Spatial Frequency Characteristics
Sub Title (in English)
Keyword(1) Blind PSNR Estimation
Keyword(2) Saliency Map
Keyword(3) AC levels
Keyword(4) SVM
1st Author's Name Takahiro KUMEKAWA
1st Author's Affiliation Graduate School of Fundamental Science and Engineering, Waseda University()
2nd Author's Name Jiro KATTO
2nd Author's Affiliation Graduate School of Fundamental Science and Engineering, Waseda University
3rd Author's Name Naofumi WADA
3rd Author's Affiliation Samsung Yokohama Research Institute Sapporo Branch
Date 2013-02-19
Paper # ITS2012-55,IE2012-135
Volume (vol) vol.112
Number (no) 434
Page pp.pp.-
#Pages 6
Date of Issue