| In recent ten years, with the development of space technique, electron optics, laser and computer science, remote sensing information is developed rapidly. Remote sensing images have a large abundance of information, which needs more space memory and high transmission speed. Therefore, image compression plays a significant role in the field of remote sensing technique.According to the characteristics of remote images, such as high resolution, little correlation, low redundancy, rich texture, etc., remote sensing images were analyzed. Combined wavelet and vector quantization with modified genetic algorithm, .the effective compressive methods are put forward in this paper and the quality of reconstructed images is improved.At first, the development of image compression and the application of wavelet transform are introduced and analyzed. Secondly, the characteristics of wavelet coefficient of image both in space and frequency, and the application of vector quantization in wavelet domain are analyzed. Moreover, contraposing to the statistical characteristics of remote images, relativities of image and statistical characteristics in wavelet domain are analyzed, and the conclusions are drawn. Finally, According to the characteristics of remote images, different kinds of vector quantization and coding are adopted, and a new method of combination of wavelet transform and the technology of vector quantization is applied and analyzed. Especially, the key technique of vector quantization is discussed and three kinds of new design method of codebook are put forward in this paper.To analyze and solve the problems of remote sensing compression, wavelet multi-resolution analysis vector quantity based on wavelet offers new methods. Therefore, the space memory and transmission problem of spatial data are settled better. Besides, requisition for the spatial data of multi-resolution is met. Therefore, they have stronger practicability and extensive application prospect.
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