Computer Science ›› 2019, Vol. 46 ›› Issue (8): 310-314.doi: 10.11896/j.issn.1002-137X.2019.08.051

• Graphics ,Image & Pattern Recognition • Previous Articles     Next Articles

Image Compression Encoding Based on Wavelet Transform and Fractal

ZHANG Jing-jing, ZHANG Ai-hua, JI Hai-feng   

  1. (School of Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,China)
  • Received:2018-06-14 Online:2019-08-15 Published:2019-08-15

Abstract: Fractal image encoding with the high compression ratio can maintain a good quality of reconstructed image.However,there are some disadvantages such as high computational complexity and long encoding time.Therefore,based on the definition of a new sub-block feature called sum of frame and point,combined with the smoothing characteristics of continuous wavelet transform,an image compression encoding on the basis of wavelet transform and fractal was proposed.This algorithm makes full use of the correlation of sub-bands,so as to improve the quality of reconstructed ima-ge.And it converts the global search into the nearest neighbor search to shorten search range and reduce encoding and decoding time.The simulation results show that compared with the basic fractal algorithm and other algorithms,the new algorithm has better performance.In addition,it not only shortens the encoding and decoding time,but also improves the reconstructed image quality

Key words: Fractal, Fractal image encoding, Image compression, Sub-block feature, Wavelet

CLC Number: 

  • TN919.81
[1]BARNSLEY M F,SLOAN A D.A better way to compress images[J].BYTE,1988,13(1):215-223.
[2]JACQUIN A E.Image coding based on a fractal theory of iterated contractive image transformations[J].IEEE Transactions on Image Processing,1992,1(1):18-30.
[3]CHEN Y Y.Fractal theory and method of image compression [M].Beijing:National Defense Industry Press,1997:1-6.(in Chinese) 陈衍仪.图像压缩的分形理论和方法[M].北京:国防工业出版社,1997:1-6.
[4]GALABOV M.Fractal image compression[C]∥Proceedings of the 4th international conference on computer systems and technologies:e-learning.ACM,2003:347-361.
[5]倪林.小波变换与图像处理[M].合肥:中国科学技术大学出版社,2010:15-28.
[6]孙延奎.小波变换与图像、图形处理技术[M].北京:清华大学出版社,2012:1-2.
[7]LOU L,LIU T S.Image compression optimization algorithm based on wavelet and fractals combined coding[J].Microelectronics & Computer,2010,27(6):145-148.
[8]LIAN H,SONG B R.Fractal coding based on wavelet for image compression[J].Journal of Shanghai Jiaotong University,2004,38(4):637-640.
[9]LI F X,SHI C J,GUAN K P.Wavelet Fractal Coding of Radar Image for VDR Storage[C]∥2012 Spring Congress on Engineering and Technology.New York:IEEE Press,2012:1-5.
[10]CHAUDHARI R E,DHOK S B.Wavelet transformed based fast fractal image compression[C]∥2014 International Conference on Circuits,Systems,Communication and Information Technology Applications (CSCITA).New York:IEEE Press,2014:65-69.
[11]PRASHANTH N,ARUN V S.Fractal image compression for HD images with noise using wavelet transforms[C]∥2015 International Conference on Advances in Computing,Communications and Informatics (ICACCI).New York:IEEE Press,2015:1194-1198.
[12]肖志云.小波域数字图像建模及其应用[M].北京:北京理工大学出版社,2014:1-10.
[13]YIN X D,TANG D,DENG J,et al.Fractal image coding using wavelet transform[J].Information and Electronic Engineering,2003,1(3):23-27.
[14]HE C J,HUANG X Y.Fast fractal image coding based on local cross trace[J].Chinese Journal of Computers,2005,28(10):1753-1758.
[15]HARTENSTEIN H,SAUPE D.Lossless acceleration of fractal image encoding via the fast Fourier transform[J].Signal Processing Image Communication,2010,16(4):383-394.
[16]LEE C K,LEE W K.Fast fractal image block coding based on local variances[J].IEEE Transactions on Image Processing,1998,7(6):888-891.
[17]李高平.分形法图像压缩编码[M].成都:西南交通大学出版社,2010:173-180.
[18]LI G P,HE C J,HUANG J J.Improving fractal image coding in terms of quality and speed[J].Computer Simulation,2006,23(5):163-166.
[19]HE C J,SHEN X N.Improving Cross Trace-Based Algorithm for Fractal Image Coding[J].Chinese Journal of Computers,2007,30(12):2156-2163.
[20]ZHANG J,ZHANG A H,WANG W W,et al.Investigation on fast fractal image encoding with sum of double cross eigenvalues[J].Computer Technology and Development,2017,27(3):159-162.
[21]WANG Q,LIANG D Q,BI S.Nearest neighbor search for fast fractal image encoding based on correlation information feature[J].Journal of Chinese Computer Systems,2011,32(6):1108-1112.
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