The Application of Wavelet Transform to Satellite Cloud Image Compression

Fang Xiang; Wang Xin

Vol.21, NO.4, 2010

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2010 > 21(4): 423-432

Fang Xiang, Wang Xin. The application of wavelet transform to satellite cloud image compression. J Appl Meteor Sci, 2010, 21(4): 423-432.

Citation:

Fang Xiang, Wang Xin. The application of wavelet transform to satellite cloud image compression. J Appl Meteor Sci, 2010, 21(4): 423-432.

Fang Xiang, Wang Xin. The application of wavelet transform to satellite cloud image compression. J Appl Meteor Sci, 2010, 21(4): 423-432.

Citation:

Fang Xiang, Wang Xin. The application of wavelet transform to satellite cloud image compression. J Appl Meteor Sci, 2010, 21(4): 423-432.

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The Application of Wavelet Transform to Satellite Cloud Image Compression

Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081

Received Date: 2009-07-10
Rev Recd Date: 2010-05-28
Publish Date: 2010-08-31

Abstract

Abstract

Different characteristics between meteorological satellite cloud images and common images are analyzed, and a compression method of meteorological satellite cloud images is proposed based on wavelet transform (WT). First, the bio-rthogonal Odegard 9/7 filter is selected, which shows better compression ability for cloud images. Using this filter, a cloud image is five step decomposed and reorganized. It's found that the wavelet coefficients of cloud image have more similarity and obvious attenuation in different steps, the wavelet coefficients are encoded using the improved 0 tree quantization algorithm. Finally, a further compression is processed for the output data streams using the adaptive arithmetic coder. The method proposed performs better in cloud image compression than other existing compression methods, e.g., the classic embedded 0 tree wavelet (EZW) introduced by Shapiro. And within the anamorphic error range, the highest ratio of cloud image compression is 40:1 for infrared image, 60:1 for water vapor image and 35:1 for visible image.
- satellite cloud image;
- image compression;
- wavelet;
- 0 tree quantization

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References(15)

Figures and Tables

图 1 原始图像灰度分布统计图

Fig. 1 Gray scale statistics in original image

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图 2 五级小波分解的低频分量系数分布图

Fig. 2 Low frequency component coefficient of five-step wavelet decomposed

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图 3 五级小波分解的水平分量系数分布

Fig. 3 Horizontal component coefficient of five-step wavelet decomposed

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图 4 基于小波变换的卫星云图压缩方案结构框图

Fig. 4 Flow chart of meteorological satellite cloud image compression method based on wavelet transform

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图 5 压缩比为30:1时恢复云图效果

Fig. 5 Recovering cloud image at compression ratio of 30:1

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表 1 各滤波器组恢复图像质量比较

Table 1 Comparison of the recovering image quality using different filters

表 2 Antoninni和Odegard恢复云图质量比较

Table 2 Comparison of Antoninni and Odegard recovering image

表 3 EZW算法和本文算法压缩效果（峰值信噪比）比较

Table 3 Comparison between EZWmethod and the method in this paper

References

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