摘要
为了度量不同失真类型的图像质量,提出一种基于小波多尺度变换的无参考质量评价方法。该方法根据自然场景统计(NSS)模型中小波多尺度变换子带能量在对数域的线性分布规律,利用失真条件下变化缓慢的高尺度子带能量预测理想图像的低尺度子带能量,同时对一些不适合失真类型进行能量补偿,最后通过量化失真图像的预测值和实际值之间的能量差异来度量图像质量。实验结果表明,该方法与主观评价方法有较好的一致性,且在总体性能上优于当前相关文献的方法。
To estimate a range of image distortions, a novel no-reference image quality assessment method is proposed based on wavelet multi-scale transformation. For natural scene statistics （NSS） model, the sub-band energy of wavelet transformation has a linear distribution with scale index. According to this principle, the energy distribution of ideal image could be predicted from high-scale sub-band energy, which was not badly affected by distortion. Meanwhile, an effective method for identifying and compensating for an inappropriate distortion was presented. Finally, the quality metric was constructed by quantifying the difference between predicted energy and real energy in degradation image. Experimental results showed that the new method was consistent with subjective assessment and outperformed the other methods.
出处
《中国图象图形学报》
CSCD
北大核心
2012年第1期33-39,共7页
Journal of Image and Graphics
基金
国家自然科学基金项目(61170120)
江苏省自然科学基金项目(B1:2011132)
关键词
无参考图像质量评价
自然场景统计模型
小波变换
多尺度预测
能量补偿
no-reference image quality assessment
natural scene statistics （NSS） model
wavelet transform
multi-scale prediction
energy compensation
