A fractal image encoding method based on statistical loss used in agricultural image compression
- 549 Downloads
Nowadays, many images of cropland are photographed and transferred by wireless sensors in agricultural automation. But one contradiction is that the recognition needs images with high quality and the transmission needs images with small sizes. So, in this paper, by extracted and analyzedthe loss in the fractal encoding,we use fractal image encoding into the compression because of its high compression ratio. To solve the most important problemin fractal image encoding method,which is its high computational complexityand long encoding time, we first use statisticalanalysis to the fractal encoding method. We create its box-plot to find the distributional of loss value. Then, we partition them to several parts and map them to the given model. After that, we present a novel method to save the loss and maintain the quality in image compression. Finally, agricultural experimental results show effectiveness of the novel method.
KeywordsImage encoding Image compression Fractal encoding Statistical loss Agricultural images
This work is supported by Grants Programs of Higher-level talents of Inner Mongolia University [No. 125126, 115117, 135103], Scientific projects of higher school of Inner Mongolia [No. NJZY13004], Natural Science Foundation of Inner Mongolia [No.2014BS0602, 2014BS0606], National Natural Science Foundation of China [No.31160253, 31360289].
The authors wish to thank Dr. Y Ma from Universityof Surrey (UK) for his help in the grammar revision andthe anonymous reviewers for their helpful comments in reviewing this paper.
Conflict of Interest
The authors declare that there are no conflict of interest in this paper.
- 2.Barnsley MF, Jacquin AE (1988) Application of recurrent iterated function systems to images, in Proceedings of the SPIE. Visual Communications and Image Processing 1001:122–131Google Scholar
- 3.Bedford T, Dekking FM, Breeuwer M (1994) Fractal coding of monochrome images[J]. Signal processing: Image communication 6(5):405–419Google Scholar
- 4.Bhavani S, Thanushkodi K G. Comparison of fractal coding methods for medical image compression[J]. IET Image Processing, 7(7)(2013) 686–693Google Scholar
- 6.Chang H T, Kuo C J. Iteration-free fractal image coding based on efficient domain pool design[J]. Image Processing, IEEE Transactions on, 9(3)(2000) 329–339.Google Scholar
- 7.DivyaUdayan JDUJ, HyungSeok Kim HSK, Jun Lee JL et al (2013) Fractal based method on hardware acceleration for natural environments[J]. Journal of Convergence 4(1):6–12Google Scholar
- 11.Yang G, Liu S, Distributed Cooperative Algorithm for Set with Negative Integer by Fractal Symmetrical Property [J]. International Journal of Distributed Sensor Networks, (2014) doi: 10.1155/2014/398583
- 16.K Falconer. Fractal Geometry: Mathematical Foundations and Applications, Second Edition[M].Wiley, Inc, 2003Google Scholar
- 17.Kim I K, Park R H. Still image coding based on vector quantization and fractal approximation[J]. Image Processing, IEEE Transactions on, 15(4)(1996) 587–597Google Scholar
- 18.Lai C M, Lam K M, Siu W C. A fast fractal image coding based on kick-out and zero contrast conditions[J]. Image Processing, IEEE Transactions on, 12(11)(2003) 1398–1403Google Scholar
- 22.S Liu, W Fu, H Deng, etc. Distributional Fractal Creating Algorithm in Parallel Environment [J], International Journal of Distributed Sensor Networks, (2013) doi:/ 10.1155/2013/281707
- 23.S Liu, W Fu, W Zhao, etc. A Novel Fusion Method by Static and Moving Facial Capture [J]. Mathematical Problems in Engineering, (2013) doi: 10.1155/2013/503924
- 24.Liu M, Liu S, Fu W, etc., Distributional Escape Time Algorithm based on GeneralizedFractal Sets in Cloud Environment [J]. Chinese Journal of Electronics (In press)Google Scholar
- 27.Monro D M, Dudbridge F. Fractal block coding of images[J]. Electronics letters, 28(11)(1992) 1053–1055Google Scholar
- 28.Rao K R, Yip P. Discrete cosine transform: algorithms, advantages, applications[M]. Academic press, Boston, 1990Google Scholar
- 30.Smart D R. Fixed point theorems[M]. CUP Archive, 1980Google Scholar
- 32.Wang X Y, Wang S G. An improved no-search fractal image coding method based on a modified gray-level transform[J]. Computers & Graphics, 32(4)(2008) 445–450Google Scholar