Efficient perceptual-based spatially varying out-of-focus blur detection
This paper proposes a blur detection algorithm that is capable of detecting and quantifying the level of spatially-varying blur by integrating directional edge spread calculation, Just Noticeable Blur (JNB) and local probability summation. The proposed method generates a blur map indicating the relative amount of perceived local blurriness. We compare the proposed method with six other state-of-the-art blur detection methods. Experimental results show that the proposed method performs the best both visually and quantitatively.