没有参考信息的摄像机图像质量评估

Lijuan Tang, Hong Lu, Ke Gu, Kezheng Sun
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引用次数: 1

摘要

模糊是评价相机图像质量的关键。它会导致高频信息的减少,从而改变图像能量。近年来对四元数奇异值分解的研究表明,四元数的奇异值及其相关向量可以捕获彩色图像的畸变,从而可以利用奇异值来评估相机图像的清晰度。在此基础上,提出了一种考虑模糊相机图像的整体颜色信息和奇异值的图像清晰度评价方法。利用纯四元数表示模糊后的相机图像的像素,得到每个块的能量。实验结果证实了盲算法在相机图像评估中的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Camera image quality assessment without reference information
Blur plays an key part in evaluating of camera image quality. It leads to decrease of high frequency information and accordingly changes the image energy. Recent researches in quaternion singular value decomposition show that the quaternion's singular values and associated vectors can capture the distortion of color images, and thus singular values can be utilized to assess the sharpness of camera image. Based on this, a novel blind quality assessment method considering the integral color information and singular values of the blurred camera image is proposed for evaluating the sharpness of camera image. Pure quaternion is utilized to represent pixels of the blurred camera image and the energy of every block are obtained. Results confirm the superiority of the proposed blind algorithm in assessing camera images.
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