A No Reference Surveillance Video Image Sharpness Assessment

Blurred images often appear in the course of surveillance video lens focusing. In order to reduce the cost of artificial detection, a no reference new method based on SSIM is proposed to assess the sharpness of surveillance video image. In the case of no reference, both Sobel operator and Gaussian low pass filter are firstly utilized to construct the reference image, and then, the SSIM of partitioned image is computed. Moreover, the quality of the image is judged via the weighted value of sub block SSIMs. The experiment results show that the proposed algorithm in this work is highly sensitive to burred image and can achieve higher accuracy than traditional methods. Hence, it can be applied to the real time surveillance video image diagnosis.