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色彩复原图像的质量评价方法 被引量:7

Quality evaluation method for color restoration image
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摘要 针对褪色文物数字化保护中色彩复原图像的质量评价问题,研究客观质量评价方法.结合峰值信噪比(PSNR)的计算优势与人眼视觉特征信息熵的结构特性,提出一种基于视觉特征信息熵的彩色图像质量评价方法.该方法建立带权值的质量评价函数和对应评价算法流程,利用归一化方法确定权值.通过评价算法流程计算复原的彩色图像与参考彩色图像的函数值,比较两者的相似程度.值越小,代表相似度越高,对应的复原彩色图像质量越好,以此客观判断色彩复原方法的优劣.实验通过四种性能差异复原方法的质量评价参数比较,表明评价结果与人眼视觉主观感受相一致,验证了所提方法的有效性. Aiming at the problem of quality evaluation of color restoration image for digital protection of faded cultural relics, the objective quality evaluation methods were researched. Combined the computational advantage of Peak Signal-toNoise Ratio( PSNR) and structure characteristic of human visual feature information entropy, a color image quality evaluation method was proposed based on information entropy of visual features. A quality evaluation function with weights and the corresponding evaluation algorithm process were established, and the weights were determined by normalization method. Then the function value for comparing the similarity between the color restoration image and the reference color image was calculated by using the evaluation algorithm process. The smaller the value was, the higher the similarity was, and the better the corresponding color restoration image quality was, which could be used for the objective judgement of color restoration method.The quality evaluation parameters of four different performance restoration methods were compared. The experimental results show that, the evaluation results are consistent with the subjective perception of human eyes, and the proposed method is effective.
出处 《计算机应用》 CSCD 北大核心 2016年第6期1673-1676,共4页 journal of Computer Applications
基金 国家自然科学基金资助项目(61373117) 陕西省教育厅产业化培育项目(2012JC24) 陕西省教育厅专项科研计划项目(15JK1656)~~
关键词 图像质量评价 人眼视觉特征 峰值信噪比 相似度 色彩复原 色彩纹理 image quality evaluation human visual feature Peak Signal-to-Noise Ratio(PSNR) similarity color restoration color texture
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  • 1HACOHEN Y, SHECHTMAN E, GOLDMAN D B, et al. Optimi- zing color consistency in photo collections [ J]. ACM Transactions on Graphics, 2013, 32(4): Article No. 38.
  • 2LIN S, RITCHIE D, FISHER M, et al. Probabilistic color-by-num- bers: suggesting pattern colorizations using factor graphs [ J]. ACM Transactions on Graphics, 2013, 32(4): Article No. 37.
  • 3BONNEEL N, SUNKAVALLI K, PARIS S, et al. Example-based video color grading [ J]. ACM Transactions on Graphics, 2013, 32 (4) : 96 -96.
  • 4BOYADZHIEV I, PARIS S, BALA K. User-assisted image compos- iting for photographic lighting [ J]. ACM Transactions on Graphics, 2013, 32(4): Article No. 36.
  • 5李娜,耿国华,龚星宇,王小凤.采用纹理图像对兵马俑褪色的复原方法[J].西安电子科技大学学报,2015,42(4):127-132. 被引量:6
  • 6仉静,桑庆兵.彩色立体图像质量评价方法[J].计算机应用,2015,35(3):816-820. 被引量:5
  • 7李鸿林,张琦,杨大伟.无参考模糊图像质量评价改进算法[J].计算机应用,2014,34(3):797-800. 被引量:10
  • 8LEE D, PLATANIOTIS K N. Towards a full-reference quality as- sessment for color images using directional statistics [ J]. IEEE Transactions on Image Processing, 2015, 24( 11): 3950 -3965.
  • 9PE1 S C, CHEN L H. Image quality assessment using human visual DOG model fused with random forest [ J]. IEEE Transactions on Im- age Processing, 2015, 24(11): 3282-3292.
  • 10OMARI M, HASSOUNI M E, ABDELOUAHAD A A, et al. A statistical reduced-reference method for color image quality assess- ment [ J]. Multimedia Tools and Applications, 2015, 74 (19) : 8685 - 8701.

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