欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
在对模糊图像边缘膨胀后进行边缘膨胀块提取的基础上，提出一种基于梯度结构相似度（GsIM）的无参考模糊图像质量评价方法（NRGSIM）。首先，将原始模糊图像经过低通滤波生成再模糊图像；之后，将原始模糊图像生成的边缘膨胀图像进行8×8分块，并将子块划分为边缘膨胀块和平滑块；然后，计算原始模糊图像和再模糊图像中所有对应到边缘膨胀图中边缘膨胀块的相应子块的GSIM；最后，平均得到整幅图像的模糊值。在4个数据库上实验结果表明，本文方法评价结果合理、稳定，更加符合人类视觉特性，与主观评分有较好的一致性，而且计算简单，取得了很好的评价效果，LIVE2数据库上的SROCC指标达到0．9641。
英文摘要：
With the popularity of the consumer electronic products,such as cell phone and other low-cost digital cameras,a large number of digital images are generated to promote interest in the study of the noreference objective image quality assessment algorithm. In this paper, based on the extracted edge dilation block from blur edge dilation image, a novel no-reference image quality assessment scheme using gradient structural similarity （NRGSIM） is proposed for quality evaluation of blurred images. In this method, firstly the re-blurred image is produced by blurring the original blurred image with a low pass filter. Then the edge dilation image is divided into 8 × 8 blocks. The sub-blocks are classified into edge dilation block and smooth block. The gradient structural similarity index is given by different weighs according to different types of blocks. Finally, the blur estimation of the whole image is produced. Experimental results on four open blur image databases show that the proposed metric is more reasonable and stable than other methods. It obtains high consistence with subjective quality evaluations and has easy calculation. It is more consistent with human visual system. So the proposed metric is appropriate for no-refer- ence blurred image quality assessment. The index of SROCC on LIVE2 database is 0. 964 1.
同期刊论文项目
同项目期刊论文
Universal blind image quality assessment using contourlet transform and singular-value decomposition
Identifying Organic-rich Marcellus Shale Lithofacies by Support Vector Machine Classifier in the App
An optimal symmetrical null space criterion of Fisher discriminant for feature extraction and recogn
期刊信息
位置：