红外模糊图像的无参考质量评价方法

图像质量评价是对图像处理算法的优劣给出合理的评估,在很多无法获取原始参考图像的应用场合中使用无参考质量评价方法。通过对红外图像结构分析得知图像所具有的不确定性往往是模糊性，而不是随机性，因此将模糊集理论中模糊熵的概念引入到红外图像质量评价中,提出一种针对红外模糊图像的无参考质量评价方法，并从算法的有效性、一致性和准确性三个方面进行比较分析。仿真实验结果表明，该方法具有计算复杂度低、运算速度快和主客观评价一致等特点，且在总体性能上优于均方误差(MSE)和峰值信噪比(PSNR)全参考图像质量评价方法。

Method of no-reference quality assessment for blurred infrared image

The image quality assessment is to give a reasonable assessment for the quality of image processing algorithm, and No-Reference (NR) quality evaluation method is applied in a lot of situations of being unable to get the original reference image. The result of structure analysis of the infrared image shows that the uncertainty of the image is fuzzy, but not random. Therefore, the concept of fuzzy entropy was introduced into the quality assessment of infrared image. A method of no-reference quality assessment for blurred infrared image was proposed, comparisons and analysis on performance of the algorithm were given from the following aspects: efficiency, consistency and accuracy. The simulation results show that this method has the characteristics of low computation complexity, fast operation speed and consistence of subjective and objective evaluations. And the general performance is better than the assessment based on Mean Squared Error (MSE) and Peak Singal-to-Noise Ratio (PSNR).