一种基于人眼对比度敏感视觉特性的图像自适应量化方法

姚军财; 刘贵忠

doi:10.11999/JEIT150848

一种基于人眼对比度敏感视觉特性的图像自适应量化方法

doi: 10.11999/JEIT150848

姚军财¹,
刘贵忠²

2.
(西安交通大学电子与信息工程学院西安 710049) ②(陕西理工学院物理与电信工程学院汉中 723000)

基金项目:

国家自然科学基金(61301237)，陕西省青年科技新星计划(2015KJXX-42)，陕西省教育厅专项科研基金(15JK1139)

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出版历程
- 收稿日期: 2015-07-16
- 修回日期: 2015-12-18
- 刊出日期: 2016-05-19

An Adaptive Quantization Method of Image Based on the Contrast Sensitivity Characteristics of Human Visual System

YAO Juncai¹,
LIU Guizhong²

2.
(The School of Electronic and Information Engineering, Xi&rsquo

Funds:

The National Natural Science Foundation of China (61301237), The Scientific and Technological New-star Plan of Shaanxi Province, China (2015KJXX-42), The Specialized Research Foundation of Shaanxi Province Education Department, China (15JK1139)

摘要

摘要: 为了提高图像的压缩比和压缩质量，结合人眼对比度敏感视觉特性和图像变换域频谱特征，该文提出一种自适应量化表的构建方法。并将该表代替JPEG中的量化表，且按照JPEG的编码算法对3幅不同的彩色图像进行了压缩仿真实验验证，同时与JPEG压缩作对比分析。实验结果表明：与JPEG压缩方法相比，在相同的压缩比下，采用自适应量化压缩后，3幅解压彩色图像的SSIM和PSNR值分别平均提高了1.67%和4.96%。表明该文提出的结合人眼视觉特性的自适应量化是一种较好的、有实用价值的量化方法。
- 图像压缩 /
- 量化 /
- 人眼视觉特性 /
- 结构相似度
Abstract: In order to improve the compression ratio and quality of the image, combined with the contrast sensitivity characteristics of human vision system and the spectrum characteristics of image in the transform domain, a method is proposed to form the adaptive quantization table in image compression. And according to the JPEG coding algorithm and replacing the quantization table in JPEG, simulations are carried out for three images by programming, whose results are compared with JPEG compression at the same time. The results show that: compared with JPEG compression, under the same compression ratio, average SSIM and PSNR of three decompressed images increase by 1.67% and 4.96% after being compressed using adaptive quantization, respectively. They show that the adaptive quantization based on HVS is a good and practical method.
- Image compression /
- Quantization /
- Human visual system characteristics /
- Structural Similarity Index Measurement (SSIM)

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参考文献(20)

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