基于小波變換和分段DPCM混合編碼的多光譜遙感圖像壓縮算法
Multispectral imagery compression by hybrid DWT and partitioning DPCM
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摘要: 多光譜遙感圖像的壓縮要利用圖像譜內及譜間的相關特性。該文在分析多光譜圖像譜內和譜間相關特性的基礎上,提出了對多光譜遙感圖像進行壓縮的分段 DPCM和 SPIHT相結合的混合壓縮算法,即首先利用分段 DPCM算法去除譜間冗余,再利用高效的 SPIHT小波壓縮算法對預測誤差圖像進行編碼。實驗取得了令人滿意的效果,證明了該算法的有效性。Abstract: Compression of multispectral imagery is based on reducing redundancies in both the spatial domain and the spectral domain. In this paper, a new hybrid compression algorithm using partitioning DPCM and SPIHT is proposed on the base of analyzing the spatial and spectral correlation features of multispectral imagery. A first-order predictor is designed for de-correlating the spectral redundancy and creating error images for later use. Because the image similarities among adjacent spectrum bands are different with the change of spectrum, the whole multispectral image sequence is partitioned into several subsets, and then DPCM predictors are designed separately for each image subset. After de-correlating spectral redundancy, a efficient wavelet coding method, SPIHT, is used to compress error images created by partitioning DPCM algorithm. The experimental results from simulated multispectral images and practical 64-band multispectral images have shown that the algorithm is fast, efficient and practical.
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