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计算机工程 ›› 2011, Vol. 37 ›› Issue (9): 229-230,233. doi: 10.3969/j.issn.1000-3428.2011.09.080

• 图形图像处理 • 上一篇    下一篇

基于DCT系数误差的图像质量评价模型

郑江云,江巨浪,李 强   

  1. (安庆师范学院物理与电气工程学院,安徽 安庆 246011)
  • 出版日期:2011-05-05 发布日期:2011-05-12
  • 作者简介:郑江云(1973-),女,讲师、硕士,主研方向:图像质量评价,水印算法;江巨浪,教授、博士;李 强,副教授、硕士
  • 基金资助:
    安徽省自然科学基金资助项目(090412065);安徽高等学校省级自然科学研究基金资助项目(KJ2009B123)

Image Quality Assessment Model Based on DCT Coefficient Error

ZHENG Jiang-yun, JIANG Ju-lang, LI Qiang   

  1. (School of Physics and Electronic Engineering, Anqing Teachers College, Anqing 246011, China)
  • Online:2011-05-05 Published:2011-05-12

摘要: 根据人眼对图像高低频失真的敏感度不同,提出一种图像质量评价模型。将图像离散余弦变换后的频率分量分为低频和高频分量,利用低频系数变化量的绝对平方和表示低频失真量、高频系数变化量相对平方和表示高频失真量,通过2个失真量相乘得到客观评价值。实验结果表明,该模型与LIVE图库上差异主观评价分的线性相关性优于峰值信噪比和结构相似度模型。

关键词: 图像质量评价, 离散余弦变换, 感觉容量, 线性相关系数

Abstract: Based on the Human Visual System(HVS) with different sensitivities in the frequency domain, this paper presents an image quality assessment model. Discrete Cosine Transform(DCT) coefficients are divided into low and high frequency components. Distortion of low frequency is showed by absolute square sum of low frequency error, but distortion of high frequency is showed by relative square sum of high frequency error. The product of two distortion is adopted as objective evaluation of quality. The model is validated with Differential Mean Opinion Score(DMOS) on LIVE database. Experimental results show that the performance of this method is superior to the algorithms of Peak Signal to Noise Ratio(PSNR) and Structural SIMilarity(SSIM).

Key words: image quality assessment, Discrete Cosine Transform(DCT), Sense Capacity(SC), linearity correlation coefficient

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