257 
Improved 
22.35 
20.6472 
18 
method 
AVG RMS - Average of the RMS for the 4096 range blocks 
to their closest domain blocks 
PSNR - Peak Signal-to-Noise Ratio of seven times iterated 
decoding image to the original image 
4. DISCUSSION 
Using the traditional method, the result shows that the 
decoding image is very similar to the original image. Though 
the quality of decoding image in the improved method is a bit 
lower, the consumed encoding time has descended to about 
18min. To different types of range blocks, we only search the 
most similar domain blocks in the same types of area. It can 
reduce the searching time and area. The experiment 
demonstrates the speed of the remote-sensing images 
encoding is improved. 
The image can also be classified into four or more types 
according to the features, and the quality of decoding image 
will be improved. However it’s more complex when finding 
the closest domain blocks for the range blocks. Meanwhile the 
consuming-time will be enhanced. How to balance the quality 
of decoding image and the consuming-time of encoding is 
still a problem. 
5. CONCLUSION 
In this paper, a traditional fractal compression algorithm is 
described and successfully applied on remote sensing image 
compression. As the exhausted consuming time, an 
improvement of the fractal compression by pre-classifying the 
image has been introduced and has a better result in the speed 
of encoding time. 
REFERENCE 
Shuguang W, 2004. The theory and development trend of 
fractal image coding. Fujian Computer, 9. pp.9-10. 
Hongmei Tang, Xia wang, 2004. The introduction of fractal 
image compression. Computer Era, 4. pp. 6-7. 
Yunsong Li, Ming Li. 2007. Fuzzy c-means clustering based on 
gray and spatial feature for image segmentation. Computer 
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Yudong Fang, Yinglin Yu, 1996. A Quick Fractal Image 
Compression Coding Method. ACTA ELECTRONICA SINICA. 
24(1). pp.28-33. 
Welstead S. 1999. Fractal and wavelet image compression 
techniques. SPIE Press. 
Wenqu Zeng, Youwei Wen,Wei Sun, 2002. Fractal Wavelet 
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ACKNOWLEDGEMENT 
Supported by the Project-sponsored by SRF for ROCS, SEM. 
mt wmb yd norfBJuqmoD o1 anoitefirniJ 
Wee Meng Woon, Anthony Tung Shuen Ho, 2000. 
Achieving high data compression of self-similar satellite 
images using fractal. IGARSS 2000. 2. pp.609-611.