北京生物医学工程

改进的基于遗传算法稀疏分解的脑CT图像压缩

Brain CT image compression with sparse decomposition based on improved genetic algorithm

作者：黄平安胡晏婷王俊

单位：南京邮电大学通信与信息工程学院(南京210003)

分类号：

出版年·卷·期（页码）：2012·31·4（356-360）

摘要：

目的提出一种新型的稀疏分解算法，对脑部CT图像进行压缩。方法本文采用改进的遗传算法(genetic algrithm，GA)与匹配追踪（matching pursuit，MP）算法相结合以实现稀疏分解，对脑部CT图像进行压缩以节约存储空间。针对原有遗传算法计算时间长、匹配率低的不足，本方法优化了迭代次数的选择、竞争、变异等操作。结果利用该算法对脑部CT图像分块压缩，使运算速度、压缩比和信噪比均得到提高。结论通过分析与实验验证，改进的方法压缩比例更大，失真更小，运行时间更短，为脑部CT图像的压缩提供了一种新方法。

Objective This paper proposes a novel sparse decomposition algorithm to compress the brain CT image. Methods Sparse decomposition is achieved with improved genetic algorithm (GA) and matching pursuit (MP) algorithm to compress the brain CT image to save storage space. For overcoming some shortcomings in original algorithm, such as long time assuming and low matching rate, the improved genetic algorithm optimizes certain operations such as selection, competition and mutation of iterations. Results We compress the brain CT images by the improved algorithm, making progress in computing speed and computational accuracy. Conclusions This improved method shows greater compression ratio, smaller distortion and shorter running time, and proposes a new method for brain CT image compression.

参考文献：

［1］ MallatS, Zhang Z, Matching pursuit with time-frequency dictionaries ［J］. IEEE Trans on Signal Processing,1993,41(12):3397-3415.
［2］Bergeau F, Mallet S. Match pursuit of images［C］. Piladelphia, PA, USA：Proceedings of IEEE-SP, 1994： 330-333.
［3］王建英，尹忠科，张春梅. 信号与图像的稀疏分解及初步应用［M］.成都：西南交通大学出版社，2006:152-168.
［4］张晓，戴冠中，徐乃平. 一种新的优化搜索算法——遗传算法［J］. 控制理论与应用，1995,12(3):265-273.
［5］Tu ZW, Chen XR, Yuille A L,et al. Image parsing unifying segmentation, detection and recognition［J］. Int J Comput Vis, 2005, 63: 113-140.
［6］Yin ZK, Xie M, Wang JY. Fast MP of images based on atom energy property［J］. Journal of University of Electronic Science and Technology of China(UESTC), 2005, 34(2):156-159.
［7］尹忠科, 王建英. 一种新的图像稀疏分解快速算法［J］. 计算机应用, 2004,24(10): 92-96.
Yin Zhongke, Wang Jianying. New fast algorithm to sparsely decompose images［J］. Journal of Computer Applications, 2004,24(10): 92-96.
［8］Wang CG, Liu JJ, Sun JX. Compression algorithm for electrocardiograms based on sparse decomposition［J］. Frontiers of Electrical and Electronic Engineering in China, 2009(3): 10-14.
［9］尹忠科,邵君, Vandergheynst P. 利用FFT实现基于MP的信号稀疏分解［J］. 电子与信息学报, 2006,28 (4): 614-618.
Yin Zhongke, Shao Jun, Vandergheynst P. MP based signal sparse decomposition with FFT［J］. Journal of Electronics & Information Technology , 2006,28 (4): 614-618.
［10］Neff R, Zakhor A. Very low bit-rate video coding based on matching pursuit. IEEE Transactions Circuits and Systems for Video Technology, 1997,1(1):158-171.
［11］Chen S, Donoho D, Saunders M. Atomic decomposition by basis on matching pursuit［J］.SIAM Journal Inform Theory, 1992,38:713-718.

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