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
Engineering and Design, 28(6), pp.1358-1363
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
Image Compression. Northeastern University Press, pp.
165-182.
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.