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壓縮感知蘋果圖像并行快速重構(gòu)方法研究
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國家自然科學基金資助項目(61271280,、61001100)和“十二五”國家科技支撐計劃資助項目(2012BAH29B04-00)


Parallel and Fast Reconstruction Algorithm for Compressed Sensing Apple Image
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    摘要:

    針對壓縮感知重構(gòu)算法耗時長而影響蘋果圖像快速獲取這一問題,分析了二維正交匹配跟蹤重構(gòu)算法的并行性,,借助GPU通用并行計算平臺,,利用CUDA技術,設計其對應的并行化重構(gòu)算法,,從而得到快速的蘋果圖像重構(gòu)方法,。實驗結(jié)果表明,并行化的算法可將蘋果圖像重構(gòu)效率提高16~35倍,,能在數(shù)秒內(nèi)恢復原始圖像,,為壓縮感知應用到果園遠程實時監(jiān)控及基于圖像的蘋果質(zhì)量快速檢測與分類等場合提供條件

    Abstract:

    With the emerging of compressed sensing (CS), it is possible to overcome the storage and transmission difficulty of the mass data sampled by traditional methods. It also provides a new way for machine vision applied to apple image sampling. However, the major shortcoming of the reconstruction algorithms for CS signals is the expensive computing time, which limits its applications to the occasions requiring fast processing. Aiming at this problem, two dimensional orthogonal matching pursuit algorithm with parallel computing is proposed for apple image reconstruction. The parallelism of the algorithm is analyzed and the parallel algorithm using CUDA technology on GPU is designed in order to achieve a fast reconstruction algorithm. Experimental results show that the parallel algorithm improves the recovery efficiency by 16 to 35 times and the apple image can be recovered in several seconds. This method provides a new technical support to remote monitoring in real time for apple garden. It can be used in the fast apple quality detection based on image as well.

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代 媛,何東健,楊 龍.壓縮感知蘋果圖像并行快速重構(gòu)方法研究[J].農(nóng)業(yè)機械學報,2014,45(9):72-78. Dai Yuan, He Dongjian, Yang Long. Parallel and Fast Reconstruction Algorithm for Compressed Sensing Apple Image[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(9):72-78.

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  • 收稿日期:2013-10-08
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  • 在線發(fā)布日期: 2014-09-10
  • 出版日期: 2014-09-10
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