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首頁(yè)> 外文期刊>Remote sensing letters >Fast orientation prediction-based discrete wavelet transform for remote sensing image compression
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Fast orientation prediction-based discrete wavelet transform for remote sensing image compression

機(jī)譯：基于快速方向預(yù)測(cè)的離散小波變換在遙感圖像壓縮中的應(yīng)用

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摘要

In this letter, a fast orientation prediction-based discrete wavelet transform (DWT) is introduced for high-spatial-resolution remote sensing image compression. The proposed fast orientation prediction-based approach is designed to improve coding performance and reduce computational complexity of the previous adaptive directional lifting method. The main contribution of the proposed approach consists of three parts: a new orientation map is designed to achieve a better transform coding performance; an orientation prediction model is presented to fast obtain the optimal transform orientation; the new fast orientation prediction-based DWT is introduced. Experimental results show that the proposed fast orientation prediction-based high-spatial-resolution remote sensing image coding technique outperforms the traditional lifting wavelet and the method based on adaptive directional lifting in coding performance, and the computational complexity of the proposed transform is far lower than that of adaptive directional lifting method.
機(jī)譯：在這封信中，介紹了一種基于快速方向預(yù)測(cè)的離散小波變換（DWT），用于高空間分辨率的遙感圖像壓縮。提出的基于快速方向預(yù)測(cè)的方法旨在提高編碼性能并降低以前的自適應(yīng)方向性提升方法的計(jì)算復(fù)雜性。所提出的方法的主要貢獻(xiàn)包括三個(gè)部分：設(shè)計(jì)新的方向圖以實(shí)現(xiàn)更好的變換編碼性能；提出了方向預(yù)測(cè)模型，以快速獲得最優(yōu)的變換方向。引入了新的基于快速方向預(yù)測(cè)的DWT。實(shí)驗(yàn)結(jié)果表明，所提出的基于快速方向預(yù)測(cè)的高空間分辨率遙感圖像編碼技術(shù)在編碼性能方面優(yōu)于傳統(tǒng)的提升小波和基于自適應(yīng)方向提升的方法，且計(jì)算復(fù)雜度遠(yuǎn)低于自適應(yīng)定向舉升方法。

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  • 來(lái)源
    《Remote sensing letters》 |2013年第12期|1156-1165|共10頁(yè)
  • 作者

    LIBAO ZHANG; BINGCHANG QIU;

  • 作者單位

    College of Information Science and Technology, Beijing Normal University, Beijing100875, China,State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing100875, China;

    College of Information Science and Technology, Beijing Normal University, Beijing100875, China;

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