|
|
|
| Sharpness metric based on histogram of strong edge width |
| ZHANG Tian-yu, FENG Hua-jun, XU Zhi-hai, LI Qi, CHEN Yue-ting |
| State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou, 310027, China |
|
|
|
Abstract This paper presented a novel no-reference sharpness/blurriness metric due to its importance in image, video applications. Based on the principle that image blurring caused edge to spread, this algorithm used a self-adapting gradient operator to compute a gradient image, which contained strong edges. The width of each strong edge was calculated and its histogram was generated. Based on the information of histogram, a distance factor was proposed. The factor was introduced into the model, which could gain the average width of strong edges by the weighted mean method, and the sharpness metric could be obtained. Comparing with the state-of-the-art edge width based sharpness evaluation, this algorithm works more efficiently. According to experimental results, the proposed method shows its good performance in content independence and high correlation with subjective assessment.
|
|
Published: 01 February 2014
|
|
|
基于强边缘宽度直方图的图像清晰度指标
针对图像清晰度评价在图像、视频领域应用的重要性,提出一种新的无参考图像清晰度评价指标.算法从图像模糊会造成边缘扩散的原理出发,通过自适应阈值的梯度算子求取含强边缘信息的图像,在得到各强边缘宽度的基础上建立强边缘宽度直方图,以此提出基于直方图信息的距离因子,通过将该因子引入到加权平均求取强边缘平均宽度的模型中,得到清晰度评价指标.实验结果表明,相比于主流的基于边缘宽度的清晰度评价方法,该方法更能够满足与图像内容无关性的要求,该方法的结果更接近于人眼主观评价.
|
|
| ［1］ LIU Han-Tao, WANG Jun-Le, REDI J, et al. An efficient no-reference metric for perceived blur ［C］∥ Proceedings of the 3rd European Workshop on Visual Information Processing. France: IEEE, 2011: 174-179.
［2］ SUN Yu, DUTHALER S, NELSON B J. Autofocusing in computer microscopy: selecting the optimal focus algorithm ［J］. Microscopy Research and Technique, 2004, 65: 139-149.
［3］ LIU Han-Tao, HEYNDERICKX I. Issues in the design of a no-reference metric for perceived blur ［C］∥ Proceedings of SPIE-IS&T Electronic Imaging 2011 and Image Quality and System Performance VIII. United States: SPIE, 2011, 7867: 0C10C8
［4］ MARICHAL X, MA Wei-Ying, ZHANG Hong-Jiang. Blur determination in the compressed domain using DCT information ［C］∥ Proceedings of the 1999 International Conference on Image Processing. Japan: IEEE, 1999: 386-390.
［5］ CAVIEDES J, GURBUZ S. No-reference sharpness metric based on local edge kurtosis ［C］∥ Proceedings of the 2002 International Conference on Image Processing. United States: IEEE, 2002: 53-56.
［6］ CAVIEDES J, OBERTI F. A new sharpness metric based on local kurtosis, edge and energy information ［J］. Signal Processing: Image Communication, 2004, 19: 147-161.
［7］ HASSEN R, ZHOU Wang, SALAMA M. No-reference image sharpness assessment based on local phase coherence measurement ［C］∥ Proceedings of the 2010 IEEE International Conference on Acoustics Speech and Signal Processing. United States: IEEE, 2010: 2434-2437.
［8］ MARZILIANO P, DUFAUX F, WINKLER S, et al. Perceptual blur and ringing metrics: application to JPEG2000 ［J］. Signal Processing: Image Communication, 2004, 19: 163-172.
［9］ WANG Xin, TIAN Bao-Feng, LIANG Chao, et al. Blind image quality assessment for measuring image blur ［C］∥ Proceedings of the 2008 Congress on Image and Signal Processing. China: IEEE, 2008: 467-470.
［10］ FERZIL R, KARAM L J. A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB) ［J］. IEEE Transactions on Image Processing, 2009, 18(4): 717-728.
［11］ NARVEKAR N D, KARAM L J. An improved no-reference sharpness metric based on the probability of blur detection ［C］∥ Proceedings of the fifth International Workshop on Video Processing and Quality Metrics for Consumer Electronics. United States: ［s. n.］, 2010.
［12］ WILLIAM K P. Digital imaging processing: PIKS scientific inside ［M］. 4th ed. United States: John Wiley & Sons, Inc., 2007.
［13］ SHEIKH H R, ZHOU Wang, CORMACK L, et al. LIVE image quality assessment database release 2 ［EB/OL］. ［2006］. http:∥live.eoe.utexas.edu/research/quality/ |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
