【摘要】：目的 CCSDS-IDC(國(guó)際空間數(shù)據(jù)系統(tǒng)咨詢委員會(huì)-圖像數(shù)據(jù)壓縮)是NASA制定的基于離散小波變換(DWT)尺度間衰減性的空間圖像數(shù)據(jù)壓縮標(biāo)準(zhǔn),適用于合成孔徑雷達(dá)(SAR)幅度圖像及各類遙感圖像的壓縮。然而,與光學(xué)圖像不同,常見的SAR圖像都是復(fù)圖像數(shù)據(jù),其在干涉測(cè)高等許多場(chǎng)合具有廣泛應(yīng)用,分析研究CCSDSIDC對(duì)SAR復(fù)圖像數(shù)據(jù)的編碼性能具有重要的應(yīng)用價(jià)值。方法由于SAR復(fù)圖像數(shù)據(jù)不具有尺度間的衰減性,因此將其用于SAR復(fù)圖像數(shù)據(jù)編碼時(shí)性能較低�？紤]到SAR復(fù)圖像數(shù)據(jù)離散小波變換(DWT)系數(shù)呈現(xiàn)出聚類特性,提出將四叉樹(QC)用于DWT域的SAR復(fù)圖像數(shù)據(jù)編碼,發(fā)現(xiàn)QC對(duì)SAR復(fù)圖像數(shù)據(jù)具有高效的壓縮性能。結(jié)果實(shí)驗(yàn)結(jié)果表明,在同等碼率下,對(duì)基于DWT的SAR復(fù)圖像數(shù)據(jù)壓縮,QC比CCSDS-IDC最多可提高幅度峰值信噪比4.4 dB,平均相位誤差最多可降低0.368;與基于方向提升小波變換(DLWT)的CCSDS-IDC相比,QC可提高峰值信噪比3.08 dB,降低平均相位誤差0.25;對(duì)其他類型的圖像壓縮,基于聚類的QC仍能獲得很好的編碼性能。結(jié)論 CCSDS-IDC對(duì)SAR復(fù)圖像數(shù)據(jù)編碼性能低下,而QC能獲得很好的編碼性能。對(duì)應(yīng)于圖像平滑分布的尺度間衰減性,其在某些特殊圖像中可能不存在,而對(duì)應(yīng)于圖像結(jié)構(gòu)分布的聚類特性總是存在的,故在基于DWT的圖像編碼算法設(shè)計(jì)中,應(yīng)優(yōu)先考慮利用小波系數(shù)的聚類特性,從而實(shí)現(xiàn)對(duì)更多種類圖像的高效編碼。
[Abstract]:Objective CCSDS-IDC (International Spatial data system Advisory Committee-Image data Compression) is a standard for spatial image data compression based on discrete wavelet transform (DWT) scale attenuation. It is suitable for the compression of synthetic Aperture Radar (SAR) amplitude images and all kinds of remote sensing images. However, unlike optical images, the common SAR images are complex image data, which are widely used in many occasions such as interferometric altimetry. It is of great value to analyze and study the encoding performance of CCSDSIDC for SAR complex image data. Methods because SAR complex image data do not have the attenuation between scales, the performance of SAR complex image data coding is low. Considering the clustering characteristics of discrete wavelet transform (DWT) coefficients of SAR complex image data, a quadtree (QC) is proposed to encode complex SAR image data in DWT domain. It is found that QC has high compression performance for SAR complex image data. Results the experimental results show that, under the same code rate, Compared with CCSDS-IDC, the maximum amplitude to noise ratio can be increased by 4.4 dB, and the average phase error can be reduced by 0.368, compared with CCSDS-IDC based on directional lifting wavelet transform (DLWT), the peak signal-to-noise ratio can be increased by 3.08 dB, and the average phase error can be reduced by using DWT-based CCSDS-IDC. Low average phase error 0. 25; for other types of image compression, QC based on clustering can still achieve good coding performance. Conclusion CCSDS-IDC has poor performance in SAR complex image coding, while QC can achieve good coding performance. Due to the inter-scale attenuation of image smoothing distribution, it may not exist in some special images, but the clustering property corresponding to image structure distribution always exists, so in the design of image coding algorithm based on DWT, Priority should be given to the clustering characteristics of wavelet coefficients in order to achieve efficient coding of more kinds of images.
【作者單位】： 西安交通大學(xué)電子與信息工程學(xué)院;高通公司圣地亞哥研究院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(61373113) 中央高校基本科研業(yè)務(wù)費(fèi)專項(xiàng)資金項(xiàng)目(xjj2012023)
【分類號(hào)】：TN957.52

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