基于人眼色彩差异化感知的图像质量评价研究

计算机工程与科学 ›› 2023, Vol. 45 ›› Issue (02): 295-303.

基于人眼色彩差异化感知的图像质量评价研究

王杨1,2,隆海燕1,2,贾曦然1,2

(1.河北工业大学电子信息工程学院，天津300401；2.河北工业大学天津市电子材料与器件重点实验室，天津300401)

收稿日期:2021-07-05 修回日期:2021-11-16 接受日期:2023-02-25 出版日期:2023-02-25 发布日期:2023-02-15
基金资助:
河北省教育厅重点项目（ZD2020304）

Research on image quality evaluation based on color differential perception of human eye

WANG Yang1,2,LONG Hai-yan1,2,JIA Xi-ran1,2

(1.College of Electronics and Information Engineering,Hebei University of Technology,Tianjin 300401;
2.Tianjin Key Laboratory of Electronic Materials & Devices,Hebei University of Technology,Tianjin 300401,China)

Received:2021-07-05 Revised:2021-11-16 Accepted:2023-02-25 Online:2023-02-25 Published:2023-02-15

摘要/Abstract

摘要： 针对显著性图像质量评价问题，参考人眼视觉对图像色彩的差异化感知，提出一种基于孪生神经网络对图像色彩对比显著区域进行质量评价的算法。首先，根据图像中的色彩对比和语义信息分别提取原始图像和失真图像中的色彩对比显著区域；然后，将原始图像和失真图像中对应的色彩区域作为子图像，以样本对的形式输入孪生神经网络；最后，计算主客观图像质量评估值的相关性。实验采用残差结构的Inception-ResNet-V2网络作为基础模型，同时增加EMD损失函数优化对图像质量的距离损失，经过Softmax层后输出图像质量评估值，并在TID2013数据集上进行了测试。结果表明，提出的算法在该数据集上性能良好。

关键词: 显著性图像质量评价, 色彩对比度, 孪生神经网络, 语义提取

Abstract: Aiming at the problem of saliency image quality evaluation, referring to the differential perception of image color by human vision, an algorithm based on siamese neural network for quality evaluation of image color contrast salient regions is proposed. Firstly, according to the color contrast and its semantic information of the image, the significant regions of color contrast are extracted respectively. Secondly, the extracted color regions are inputted into the siamese neural network as sub-images in the form of sample pairs. Finally, the correlation between the subjective and objective image quality evaluation values is calculated. In the experiment, the Inception-ResNet-V2 network with residual structure is used as the basic model. The EMD loss function is introduced to optimize the distance loss. After being filtered through the Softmax layer, the image quality evaluation value is obtained. Tests are carried out on the TID2013 dataset and the test results show that the proposed algorithm has good performance on this dataset.

Key words: saliency image quality evaluation, color contrast, siamese neural network, semantic extraction

王杨, 隆海燕, 贾曦然, . 基于人眼色彩差异化感知的图像质量评价研究[J]. 计算机工程与科学, 2023, 45(02): 295-303.

WANG Yang, LONG Hai-yan, JIA Xi-ran, . Research on image quality evaluation based on color differential perception of human eye[J]. Computer Engineering & Science, 2023, 45(02): 295-303.