HLFSIM: Objective image quality metric based on ROI analysis

2012 IEEE International Carnahan Conference on Security Technology (ICCST) Pub Date : 2012-12-31 DOI:10.1109/CCST.2012.6393587

Petr Dostál, Lukáš Krasula, M. Klima

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引用次数: 5

Abstract

The image/video quality is a key issue in security video systems. Therefore the objective image/video quality criteria are extensively studied. In this paper, the novel full reference objective metric for image quality assessment is proposed. This metric is based on FSIM. The ROI detection is embedded in order to improve the performance. For ROI estimation, the ground truth data together with two different algorithms were used and compared - The security and multimedia images from LIVE database were used for performance evaluation. The correlation between the objective and subjective tests of multimedia images was calculated using Pearson's and Spearman Rank Order Correlation Coefficient. For performance comparison the state-of-the-art full reference objective image quality metrics were used; PSNR, SSIM, MS-SSIM, VIF and FSIM. In our previous paper, the importance of demosaicing technique and ROI has been shown. This paper continues in this topic and implements new full reference objective metrics for the reconstructed image quality evaluation. The results reveal that the ROI controlled by bottom-up mechanism can be used for performance improvement.

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HLFSIM:基于ROI分析的客观图像质量度量

图像/视频质量是安防视频系统中的一个关键问题。因此，客观的图像/视频质量标准被广泛研究。本文提出了一种新的图像质量评价全参考客观度量。该指标基于FSIM。为了提高性能，嵌入了ROI检测。在ROI估计中，使用了地面真实数据和两种不同算法进行比较，并使用LIVE数据库中的安全图像和多媒体图像进行性能评估。采用Pearson’s和Spearman秩序相关系数计算多媒体图像的客观和主观测试之间的相关性。为了进行性能比较，使用了最先进的全参考客观图像质量指标;PSNR, SSIM, MS-SSIM, VIF和FSIM。在之前的文章中，我们已经说明了去马赛克技术和ROI的重要性。本文在此基础上，提出了一种新的全参考客观指标来评价重建图像的质量。结果表明，由自下而上机制控制的ROI可以用于绩效改进。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2012 IEEE International Carnahan Conference on Security Technology (ICCST)

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