首页> 外文会议>第21届国际摄影测量与遥感大会(ISPRS 2008)论文集 >AN IMPROVED METHOD OF REMOTE SENSING IMAGE COMPRESSION BASED ON FRACTAL AND WAVELET DOMAIN
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AN IMPROVED METHOD OF REMOTE SENSING IMAGE COMPRESSION BASED ON FRACTAL AND WAVELET DOMAIN

机译:基于分形和小波域的改进的遥感图像压缩方法

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摘要

One of the efficient solutions for data transmission and storage of huge remote sensing images is the high-fidelity and rapid compression. The hybrid algorithms based on fractal coding and wavelet transformation have already been developed and are becoming very popular at present. In this paper, an improved method of remote sensing image compression based on fractal coding and wavelet domain is proposed. Firstly, the method uses the wavelet-transformation to create the similarity between sub-bands of an image, and the fractal algorithm is exploited to code for adjacent high-frequency bands with similarity character, it is must be mentioned that some improvement has been used to speed up searching for similarity blocks during the step. Consequently, fractal iterative decoding and wavelet inverse transform are applied to reconstruct the image. From the above, it can be concluded the method proposed in this paper not only makes full use of the characteristic of wavelet multi-resolution, but also considers the self-similarity among objects. Finally, some experiments have been given, and the results demonstrates that the method can do well in the remote sensing image compression, less losing of the image information and more recovering of image quality. Moreover, ensuring the signal-noise ratio of the image, it can better increase the image coding efficiency.
机译:高保真和快速压缩是用于巨大的遥感图像的数据传输和存储的有效解决方案之一。基于分形编码和小波变换的混合算法已经被开发出来,并且在当前非常流行。提出了一种基于分形编码和小波域的遥感图像压缩方法。首先,该方法利用小波变换来创建图像子带之间的相似性,并利用分形算法对具有相似性的相邻高频带进行编码,必须指出的是,已经进行了一些改进。加快在此步骤中搜索相似性块的速度。因此,应用分形迭代解码和小波逆变换来重建图像。由上可知,本文提出的方法不仅充分利用了小波多分辨率的特征,而且考虑了物体之间的自相似性。最后,进行了一些实验,结果表明该方法在遥感图像压缩中效果很好,图像信息的丢失更少,图像质量的恢复更多。而且,在保证图像信噪比的前提下,可以更好地提高图像编码效率。

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