A No-Reference Sharpness Metric Based on Structured Ringing for JPEG2000 Images

Zhipeng Cao, Zhenzhong Wei, Guangjun Zhang
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引用次数: 1

Abstract

This work presents a no-reference image sharpness metric based on human blur perception for JPEG2000 compressed image. The metric mainly uses a ringing measure. And a blurring measure is used for compensation when the blur is so severe that ringing artifacts are concealed. We used the anisotropic diffusion for the preliminary ringing map and refined it by considering the property of ringing structure. The ringing detection of the proposed metric does not depend on edge detection, which is suitable for high degraded images. The characteristics of the ringing and blurring measures are analyzed and validated theoretically and experimentally. The performance of the proposed metric is tested and compared with that of some existing JPEG2000 sharpness metrics on three widely used databases. The experimental results show that the proposed metric is accurate and reliable in predicting the sharpness of JPEG2000 images.
基于结构化环的JPEG2000图像无参考清晰度度量
本文提出了一种基于人类模糊感知的JPEG2000压缩图像的无参考图像清晰度度量。该度量主要使用振铃度量。当图像模糊严重,导致环形伪影被掩盖时,采用模糊补偿措施。我们采用各向异性扩散法建立了初步的环形图,并考虑环形结构的性质对其进行了细化。该度量的振铃检测不依赖于边缘检测,适用于高退化图像。分析了振铃和模糊措施的特点,并进行了理论和实验验证。在三个广泛使用的数据库上测试了所提度量的性能,并与现有的一些JPEG2000清晰度度量进行了比较。实验结果表明,该度量方法能够准确、可靠地预测JPEG2000图像的清晰度。
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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