Abstract
An objective blurriness model is useful in various image processing applications. Especially, a no-reference model is expected as a highly desirable approach due to its applicability to wide range of applications. Blurriness of an image is known as to be commonly induced by the attenuation of spatial high-frequency and thus most conventional researches focused on a model estimating the amount of spatial high-frequency. However, the human-perceived blurriness might be varied across image contents. Very few researches have been investigated the human visual system model for the blurriness perception. To address the lack of an efficient model, this paper presents the blurriness perception model designed as a spatially varying function based on the inherent sharpness. Pixel-wise perceptual blurriness is computed employing the blurriness perception model and then integrated into an overall blurriness index using saliency information. The experimental comparisons with state-of-the-arts blurriness models for extensive public databases show that the proposed model is well-correlated with the subjective scores across different content of images, and outperforms the compared models.
| Original language | English |
|---|---|
| Title of host publication | 2014 IEEE International Conference on Image Processing, ICIP 2014 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 580-584 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781479957514 |
| DOIs | |
| Publication status | Published - 2014 Jan 28 |
Publication series
| Name | 2014 IEEE International Conference on Image Processing, ICIP 2014 |
|---|
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All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
Cite this
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No-reference perceptual blur model based on inherent sharpness. / Ryu, Seungchul; Sohn, Kwanghoon.
2014 IEEE International Conference on Image Processing, ICIP 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 580-584 7025116 (2014 IEEE International Conference on Image Processing, ICIP 2014).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - No-reference perceptual blur model based on inherent sharpness
AU - Ryu, Seungchul
AU - Sohn, Kwanghoon
PY - 2014/1/28
Y1 - 2014/1/28
N2 - An objective blurriness model is useful in various image processing applications. Especially, a no-reference model is expected as a highly desirable approach due to its applicability to wide range of applications. Blurriness of an image is known as to be commonly induced by the attenuation of spatial high-frequency and thus most conventional researches focused on a model estimating the amount of spatial high-frequency. However, the human-perceived blurriness might be varied across image contents. Very few researches have been investigated the human visual system model for the blurriness perception. To address the lack of an efficient model, this paper presents the blurriness perception model designed as a spatially varying function based on the inherent sharpness. Pixel-wise perceptual blurriness is computed employing the blurriness perception model and then integrated into an overall blurriness index using saliency information. The experimental comparisons with state-of-the-arts blurriness models for extensive public databases show that the proposed model is well-correlated with the subjective scores across different content of images, and outperforms the compared models.
AB - An objective blurriness model is useful in various image processing applications. Especially, a no-reference model is expected as a highly desirable approach due to its applicability to wide range of applications. Blurriness of an image is known as to be commonly induced by the attenuation of spatial high-frequency and thus most conventional researches focused on a model estimating the amount of spatial high-frequency. However, the human-perceived blurriness might be varied across image contents. Very few researches have been investigated the human visual system model for the blurriness perception. To address the lack of an efficient model, this paper presents the blurriness perception model designed as a spatially varying function based on the inherent sharpness. Pixel-wise perceptual blurriness is computed employing the blurriness perception model and then integrated into an overall blurriness index using saliency information. The experimental comparisons with state-of-the-arts blurriness models for extensive public databases show that the proposed model is well-correlated with the subjective scores across different content of images, and outperforms the compared models.
UR - http://www.scopus.com/inward/record.url?scp=84983154308&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983154308&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2014.7025116
DO - 10.1109/ICIP.2014.7025116
M3 - Conference contribution
AN - SCOPUS:84983154308
T3 - 2014 IEEE International Conference on Image Processing, ICIP 2014
SP - 580
EP - 584
BT - 2014 IEEE International Conference on Image Processing, ICIP 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -