本文選題：壓縮感知 + 編碼矩陣��； 參考：《航天返回與遙感》2017年05期

【摘要】：壓縮感知作為突破傳統(tǒng)奈奎斯特定理限制的一種信號(hào)處理的新途徑,近年來(lái)受到了諸多研究領(lǐng)域的廣泛關(guān)注,特別是在遙感成像方面。該理論中,編碼矩陣的設(shè)計(jì)起著非常關(guān)鍵的作用。事實(shí)上,原始信號(hào)能否被有效壓縮,接收端能否將原始信號(hào)精確重構(gòu),都依賴于編碼矩陣設(shè)計(jì)的優(yōu)劣。然而,目前常見(jiàn)的編碼矩陣普遍不利于硬件的實(shí)現(xiàn),尤其是遙感成像中的采樣更是要求計(jì)算簡(jiǎn)單、省電的設(shè)備,所以這是影響壓縮感知在遙感成像領(lǐng)域推廣的主要障礙之一。文章的研究目的是找到一種新的編碼矩陣,既有良好的壓縮感知采樣性能,又有利于針對(duì)遙感應(yīng)用的硬件實(shí)現(xiàn)和降低硬件成本。鑒于分塊壓縮感知在重構(gòu)時(shí)的優(yōu)勢(shì)即提升重構(gòu)速度和品質(zhì),提出了基于分塊的二級(jí)尺度編碼矩陣設(shè)計(jì),即在第一次分塊的基礎(chǔ)上再次分塊,并以此基礎(chǔ)設(shè)置編碼矩陣。通過(guò)實(shí)驗(yàn)?zāi)M實(shí)際的硬件采樣過(guò)程,分析所設(shè)計(jì)編碼矩陣的不足之處,并對(duì)其進(jìn)一步優(yōu)化,使得所搭建的硬件成像平臺(tái)中對(duì)圖像采樣的數(shù)據(jù)可以在終端進(jìn)行高品質(zhì)的重構(gòu)。
[Abstract]:As a new way of signal processing which is restricted by the traditional Nyquist theorem, compressed sensing has received extensive attention in many fields of research in recent years, especially in remote sensing imaging. In this theory, the design of the coding matrix plays a very important role. In fact, whether the original signal can be effectively compressed and whether the receiver will be able to be the original or not The accurate reconstruction of the initial signal depends on the design of the coding matrix. However, the common coding matrix is generally not conducive to the implementation of the hardware. Especially, the sampling in remote sensing imaging is more important for computing simple and electricity saving devices. Therefore, this is one of the main obstacles that influence the promotion of compressed sensing in remote sensing image field. In order to find a new coding matrix, it not only has good compressed sensing sampling performance, but also is beneficial to hardware implementation and hardware cost reduction for remote sensing applications. In view of the superiority of the block compression perception in the reconstruction of the reconstruction speed and quality, a block based two level scale coding matrix is designed, that is, in the first block. On the basis of this, the coding matrix is set up again and the coding matrix is set on this basis. By simulating the actual hardware sampling process, the shortcomings of the designed coding matrix are analyzed, and the further optimization is made, which makes the data of the image sampled in the hardware imaging platform can be reconstructed with high quality at the final end.
【作者單位】： 南京理工大學(xué)計(jì)算機(jī)學(xué)院;
【基金】：國(guó)家自然科學(xué)基金(61273251)
【分類號(hào)】：TN911.73

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