期刊文献+

视频监控应用中图像压缩算法的研究

Research on Image Compression Algorithm of Video Surveillance Applications
下载PDF
导出
摘要 基于DCT的JPEG图像压缩算法是视频监控应用中的核心技术。虽然传统的DCT其画质有保障,但其复杂度较大,不利于视频实时传输。所以,文中主要研究的目的就是降低其算法复杂度,并且保证传输图像的质量。基于图像能量都集中于DCT系数的低频部分这一特性,文中提出局部截取法,可以快速得到图像的重要信息,在没有明显影响图像质量的情况下,使得二维8*8DCT的计算量大幅降低。由实验论证,在PSNR没有明显下降的情况下,算法复杂度明显降低。 DCT-based JPEG image compression algorithm is the core technology of video surveillance applications. Picture quality of conventional DCT is guaranteed,but its complexity is greater, which is not conducive to real-time video transmission. Therefore, the main purpose is to reduce the complexity of the algorithm, and to ensure the transmission quality of the image. Based on this feature that image energy is concentrated in the low-frequency portion of the DCT coefficient,propose a partial intercept method which makes the calcula- tion of 8 * 8 DCT be significantly reduced, and you can quickly get important information about the image. The results of experiments show that in the case of no significant decrease in PSNR,the algorithm complexity is significantly reduced.
出处 《计算机技术与发展》 2014年第4期84-87,91,共5页 Computer Technology and Development
基金 国家自然科学基金资助项目(61105082)
关键词 离散余弦变换 JPEG图像压缩算法 峰值信噪比 Discrete Cosine Transform (DCT) JPEG image compression algorithm PSNR
  • 相关文献

参考文献11

二级参考文献56

  • 1马宁,朱福萌,尹志军,蒋林辉.改进游程编码在天气雷达数据压缩中的应用[J].解放军理工大学学报(自然科学版),2004,5(6):88-90. 被引量:19
  • 2李秀敏,万里青,周拥军.基于MATLAB的DCT变换在JPEG图像压缩中的应用[J].电光与控制,2005,12(2):64-67. 被引量:17
  • 3张健.基于离散余弦变换数据压缩算法的图像处理应用[J].科技咨询导报,2007(8):57-58. 被引量:2
  • 4Pham T, Figueiredo R. Maximum likelihood estimation of a class of non-Gaussian densities with application to Ip deconvolutions [J]. IEEE Trans Acoust, Speech, Signal Process, 1999, 37(1): 73-82.
  • 5Lam E, Goodman J. A mathematical analysis of the DCT coefficient distributions for images[J]. IEEE Trans Image Process, 2000, 4: 1661-1666.
  • 6Edue T, Grisel R, Cherifim H, et al. On the distribution of the DCT coefficients [C]//Proc IEEE ICASSP. Adelaide, Australia, 2004 : V365 - V368.
  • 7Rec. J. 143. User requirements for Objective Perceptual Video Quality Measurements in Digital Cable Television [S]. ITU- T, May 2000.
  • 8Wang Z, Bovil A. Blind measurement of blocking artifacts in images [J]. Int Conf Image Process, 2000, Ⅲ: 981 - 984.
  • 9Wu H, Yuen M. A generalized block-edge impairment metric for video coding[J]. IEEE Signal Precess Lett, 1997, 4 (1) : 317 - 320.
  • 10Turaga D, Chen Y, Caviedes J. No reference PSNR estimation for compressed pictures [J]. Signal Process Image Commun, 2004, 19: 173-184.

共引文献114

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部