Abstract
This paper focuses on no-reference image sharpness/blurriness metrics due to their importance in image, video, and biomedical applications. Simulation results show that existing no-reference objective image sharpness metrics fail to predict correctly the sharpness of images in the presence of noise. A noise-immune wavelet-based sharpness metric is proposed based on the Lipschitz regularity for differentiating between edges and noise singularities. Comparison results reveal the superiority of the proposed method when dealing with a moderate noisy environment.
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