欢迎登录材料期刊网

材料期刊网

高级检索

为了使图像压缩后的效果更加符合人眼感知特性,提出了一种结合人眼对比度敏感视觉特性的图像压缩算法.算法首先结合视觉特性和图像变换域频谱系数特征,提出一种图像的角频率的计算方法,并依据计算的角频率提出一种人眼觉察图像最小误差阈值的计算方法;然后以此阈值作为量化步长,提出一种图像变换域频谱系数的量化方法;最后采用霍夫曼编码算法进行编解码,实现图像的压缩.并对三幅彩色图像进行了仿真实验,结果表明:与JPEG技术相比,三幅彩色图和各分量图的平均压缩比、PSNR和 SSIM依次提高了10.4807%、6.9879%和2.6494%.表明提出的结合人眼视觉特性的图像压缩算法是一种较好的、有实用价值的压缩算法.

In order to make the compressed images satisfy more with the human visual perception char-acteristics,a color image compression algorithm combined the human visual contrast sensitivity char-acteristics is proposed.Firstly,combining the characteristics of human visual contrast sensitivity and spectrum coefficients in transform domain of image,a method for calculating the angular frequencies of the images is proposed,and the calculating method of minimum error threshold of human eye detec-ting images is proposed according to the angular frequencies.Then taking the threshold as quantiza-tion step size,a method is proposed to quantize spectrum coefficients in transform domain of image. Finally Huffman coding algorithm is adopted to carry out encoding and decoding to realize image com-pression.And the simulation experiments for three color images is carried out .The results show that the average compression ratio,PSNR and SSIM of three color images and each component of the image are increased by 10.480 7%,6.987 9% and 2.649 4% respectively,compared with the technol-ogy of JPEG.It indicates that the image compression algorithm combined the human visual character-istics is better and more practical.

参考文献

[1] 李昌国;郭科.应用自适应预测器排序的三阶预测高光谱图像无损压缩[J].光学精密工程,2014(3):760-769.
[2] A. Benoit;A. Caplier;B. Durette;J. Herault.Using Human Visual System modeling for bio-inspired low level image processing[J].Computer vision and image understanding: CVIU,20107(7):758-773.
[3] 酉霞;陈菲;贾小林;刘雨娇;杨勇.字典学习中字典尺度对 DICOM 图像压缩的影响[J].液晶与显示,2015(6):1045-1051.
[4] Douak, F.;Benzid, R.;Benoudjit, N..Color image compression algorithm based on the DCT transform combined to an adaptive block scanning[J].AEU: Archiv fur Elektronik und Ubertragungstechnik: Electronic and Communication,20111(1):16-26.
[5] Zhongkang Lu;Lin W.;Yang X.;EePing Ong;Susu Yao.Modeling visual attention's modulatory aftereffects on visual sensitivity and quality evaluation[J].IEEE Transactions on Image Processing,200511(11):1928-1942.
[6] Ferda Ernawan;Nur Azman Abu;Nanna Suryana.An Optimal Tchebichef Moment Quantization Using Psychovisual Threshold for Image Compression[J].Advanced Science Letters,20141(1):70-74.
[7] Zhang, Y.;Cao, H.;Jiang, H.;Li, B..Visual Distortion Sensitivity Modeling for Spatially Adaptive Quantization in Remote Sensing Image Compression[J].IEEE geoscience and remote sensing letters,20144(4):723-727.
[8] 王宇庆;王索建.红外与可见光融合图像的质量评价[J].中国光学,2014(3):396-401.
[9] Dai, W.;Xiong, H.;Wang, J.;Zheng, Y.F..Large Discriminative Structured Set Prediction Modeling With Max-Margin Markov Network for Lossless Image Coding[J].IEEE Transactions on Image Processing,20142(2):541-554.
[10] Zhou Wang;Bovik A.C.;Sheikh H.R.;Simoncelli E.P..Image quality assessment: from error visibility to structural similarity[J].IEEE Transactions on Image Processing,20044(4):600-612.
[11] 卫沛锋;刘欣悦;林旭东;董磊;王鸣浩.自适应光学系统校正后实际分辨率评价指标[J].中国光学,2014(4):672-678.
上一张 下一张
上一张 下一张
计量
  • 下载量()
  • 访问量()
文章评分
  • 您的评分:
  • 1
    0%
  • 2
    0%
  • 3
    0%
  • 4
    0%
  • 5
    0%