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

机译:基于结构化铃声的JPEG2000图像无参考清晰度指标

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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.
机译:这项工作提出了基于人为JPEG2000压缩图像的模糊感知的无参考图像清晰度度量。度量标准主要使用振铃量度。当模糊非常严重以至于掩盖了振铃伪影时,将使用模糊措施进行补偿。我们将各向异性扩散用于初步的振铃图,并考虑到振铃结构的性质对其进行了细化。所提出度量的振铃检测不依赖于边缘检测,该边缘检测适用于高降级图像。从理论上和实验上对振铃和模糊措施的特性进行了分析和验证。测试了所提出度量的性能,并与三个广泛使用的数据库上的某些现有JPEG2000清晰度度量进行了比较。实验结果表明,所提出的度量标准在预测JPEG2000图像的清晰度方面是准确可靠的。

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