Full-reference and reduced-reference quality metrics based on SIFT
Full-reference and reduced-reference quality metrics based on SIFT
复制标题
DOI：
10.1109/icassp.2014.6853578
复制
发表时间：
2014-05
期刊：
影响因子：
--
通讯作者：
J. Farah;Marie-Rita Hojeij;Jihad Chrabieh;F. Dufaux
中科院分区：
文献类型：
--
作者：
J. Farah;Marie-Rita Hojeij;Jihad Chrabieh;F. Dufaux
在过去的十年中，一个重要的研究工作一直致力于实现客观的图像质量评估指标，有效地反映人类的感知。因此，本文的目的是提出新的客观指标，满足图像质量评估领域的需求。为此，我们提出了两个主要的全参考（FR）的质量指标，然后适应他们在这样一种方式，构成几个新的减少参考（RR）的质量指标，在完整的参考图像是不可用的情况下。我们评估了JPEG、JPEG2000、高斯模糊、AWGN和对比度变化等五种失真对图像质量的影响。建议的度量是基于尺度不变特征变换（SIFT）点的数量，未配对和失真图像之间的SIFT匹配的数量，以及结构相似性指数（SSIM）。为了验证我们提出的指标，我们计算我们的指标的分数和主观评价结果之间的相关性。结果表明，高相关性和更好的质量范围相比，众所周知的指标，以及良好的鲁棒性减少参考的情况。
In the last decade, an important research effort has been dedicated to implement objective image quality assessment metrics that reflect effectively human perception. Therefore, the aim of this paper is to propose new objective metrics that fulfill the demands of the image quality assessment field. For this sake, we propose two main full-reference (FR) quality metrics, and then adapt them in such a way to constitute several new reduced-reference (RR) quality metrics, for the case where the complete reference image is not available. We evaluate the influence of five types of distortion such as JPEG, JPEG2000, Gaussian Blur, AWGN, and Contrast change, on the image quality. The proposed metrics are based on the number of Scale-Invariant Feature Transform (SIFT) points, the number of SIFT matches between the unpaired and distorted images, and the Structural Similarity index (SSIM). In order to validate our proposed metrics, we compute the correlation between our metrics' scores and the subjective evaluation results. The results show a high correlation and a better quality range compared to well-known metrics, as well as a good robustness to reduced-reference situations.