一種基于人眼對(duì)比度敏感視覺特性的圖像自適應(yīng)量化方法

姚軍財(cái); 劉貴忠

doi:10.11999/JEIT150848

一種基于人眼對(duì)比度敏感視覺特性的圖像自適應(yīng)量化方法

doi: 10.11999/JEIT150848

姚軍財(cái)¹,
劉貴忠²

2.
(西安交通大學(xué)電子與信息工程學(xué)院西安 710049) ②(陜西理工學(xué)院物理與電信工程學(xué)院漢中 723000)

基金項(xiàng)目:

國家自然科學(xué)基金(61301237)，陜西省青年科技新星計(jì)劃(2015KJXX-42)，陜西省教育廳專項(xiàng)科研基金(15JK1139)

計(jì)量
- 文章訪問數(shù): 1810
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- 被引次數(shù): 0
出版歷程
- 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: 為了提高圖像的壓縮比和壓縮質(zhì)量，結(jié)合人眼對(duì)比度敏感視覺特性和圖像變換域頻譜特征，該文提出一種自適應(yīng)量化表的構(gòu)建方法。并將該表代替JPEG中的量化表，且按照J(rèn)PEG的編碼算法對(duì)3幅不同的彩色圖像進(jìn)行了壓縮仿真實(shí)驗(yàn)驗(yàn)證，同時(shí)與JPEG壓縮作對(duì)比分析。實(shí)驗(yàn)結(jié)果表明：與JPEG壓縮方法相比，在相同的壓縮比下，采用自適應(yīng)量化壓縮后，3幅解壓彩色圖像的SSIM和PSNR值分別平均提高了1.67%和4.96%。表明該文提出的結(jié)合人眼視覺特性的自適應(yīng)量化是一種較好的、有實(shí)用價(jià)值的量化方法。
- 圖像壓縮 /
- 量化 /
- 人眼視覺特性 /
- 結(jié)構(gòu)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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參考文獻(xiàn)(20)

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