基于Karhunen-Loeve和小波變換的多光譜圖像三維集合嵌入塊編碼壓縮算法

吳家驥; 吳成柯

基于Karhunen-Loeve和小波變換的多光譜圖像三維集合嵌入塊編碼壓縮算法

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出版歷程
- 收稿日期: 2004-03-15
- 修回日期: 2004-12-08
- 刊出日期: 2005-08-19

Compression of Multispectral Image Using Three-Dimensional Embedded Block Coding Algorithm Based on Karhunen-Loeve and Wavelet Transforms

摘要

摘要: 目前多光譜成像已被廣泛應(yīng)用在遙感領(lǐng)域中,但巨量的多光譜圖像數(shù)據(jù)導(dǎo)致存儲(chǔ)和傳輸?shù)睦щy,這就需要對(duì)多光譜圖像數(shù)據(jù)進(jìn)行高效的壓縮.該文提出了一種新的多光譜圖像壓縮算法(KLT/WT-3DSPECK),首先利用二維小波變換(2DWT)去除多光譜圖像的空間相關(guān)冗余,然后利用Karhunen-Loeve變換(KLT)減少頻域的相關(guān)性,最后對(duì)變換后的系數(shù)利用改進(jìn)的三維集合塊分裂算法(3DSPECK)進(jìn)行編碼.根據(jù)變換后子帶能量分布的特點(diǎn),提出了新的3D八度音符分裂方法(octave partitioning)和改進(jìn)的集合零塊分裂算法.為了加速本文算法和優(yōu)化嵌入碼流的率失真性能,還給出了一種零塊優(yōu)化排序的快速算法.對(duì)兩組多光譜和超光譜圖像的測(cè)試表明,該算法不僅明顯優(yōu)于KLT/WT-3DSPIHT算法,也遠(yuǎn)優(yōu)于基于3D小波變換的AT-3DSPIHT和3DSPECK等算法,同時(shí)該算法還支持圖像的漸進(jìn)傳輸.
- 多光譜圖像壓縮; 嵌入編碼; 零塊編碼; SPECK; 小波變換; Karhunen-Loeve變換
Abstract: Multispectral imaging has been widely used in the field of remote sensing. The storage and transmission of large volumes of multispectral data have become significant concerns. Therefore efficient compression is required for storage and transmission. This paper proposes a new multispectral image data compression algorithm （KLT/WT3DSPECK）. First, a 2D wavelet transform is applied to reduce the spatial redundancies. Next a Karhunen-Loeve Transform （KLT） is used to remove the correlation between adjacent spectral bands. Finally a modified 3DSPECK method is proposed and is used to code the transformed coefficients. According to the distribution of energy of the transformed coefficients, a novel 3D octave partitioning scheme and an improved set partitioning zeroblock method are presented. To accelerate the speed and optimize the rate-distortion performance of the embedded bit stream, a fast algorithm of the optimal zeroblock sorting is given. Numerical experiments on two sample multispectral images show that the proposed KLT/WT-3DSPECK algorithm outperforms either the KLT/WT-3DSPIHT algorithm or the 3DWT-based AT-3DSPIHT and 3DSPECK algorithms. Besides having high performance, the KLT/WT-3DSPECK algorithm support progressive transmission.

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參考文獻(xiàn)(1)

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