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http://dx.doi.org/10.5909/JBE.2020.25.1.58

Texture-aware Blur Detection  

Jeong, Chanho (Department of Electrical and Electronics Engineering, Konkuk University)
Kim, Wonjun (Department of Electrical and Electronics Engineering, Konkuk University)
Publication Information
Journal of Broadcast Engineering / v.25, no.1, 2020 , pp. 58-66 More about this Journal
Abstract
The blur effect, which is generated by various external factors such as out-of-focus and object movement, degrades high-frequency components in the original sharp image. Based on this observation, we propose a novel method for blur detection using textural features. Specifically, the proposed method simultaneously adopts learning-based and watershed-based textural features, which effectively detect the blur on various situations. Moreover, we employ the region-based refinement to improve the processing time while also increasing detection accuracy. Experimental results demonstrate that the proposed method provides the competitive performance compared to previous approaches in literature.
Keywords
Blur detection; high-frequency components; learning-based textural features; watershed-based textural features;
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