發(fā)布時(shí)間：2018-03-06 12:44

  本文選題：編碼曝光　切入點(diǎn)：圖像復(fù)原　出處：《國(guó)防科學(xué)技術(shù)大學(xué)》2014年博士論文　論文類(lèi)型：學(xué)位論文

【摘要】：遙感成像系統(tǒng)信息集成需要對(duì)各種平臺(tái)、各種波段的成像系統(tǒng)進(jìn)行有效地整合與統(tǒng)一,要求各分系統(tǒng)能夠提供足夠精確的信息源。基于無(wú)人機(jī)平臺(tái)的可見(jiàn)光遙感成像系統(tǒng)作為信息集成的重要組成部分,其成像運(yùn)動(dòng)模糊問(wèn)題會(huì)影響到整個(gè)遙感成像系統(tǒng)的決策支持能力。隨著無(wú)人機(jī)技術(shù)的快速發(fā)展,基于無(wú)人機(jī)平臺(tái)的遙感成像系統(tǒng)在遙感成像領(lǐng)域發(fā)揮著越來(lái)越重要的作用。因此,解決遙感系統(tǒng)信息集成中的無(wú)人機(jī)可見(jiàn)光遙感圖像運(yùn)動(dòng)模糊問(wèn)題具有迫切的現(xiàn)實(shí)需求。無(wú)人機(jī)可見(jiàn)光遙感圖像運(yùn)動(dòng)模糊主要是由成像設(shè)備與拍攝場(chǎng)景之間大尺度相對(duì)運(yùn)動(dòng)引起的。針對(duì)圖像的運(yùn)動(dòng)模糊,當(dāng)前主要有兩種解決思路:一是采用后處理方式的圖像復(fù)原算法;二是采用高速成像技術(shù)。然而,傳統(tǒng)模糊圖像復(fù)原是一種病態(tài)問(wèn)題,對(duì)于大尺度的運(yùn)動(dòng)模糊圖像的復(fù)原效果不夠理想。高速成像技術(shù)需要特殊硬件設(shè)備的支持,價(jià)格昂貴且應(yīng)用范圍有限。近年來(lái),計(jì)算攝影領(lǐng)域中發(fā)展出一種編碼曝光成像技術(shù),創(chuàng)造性地將病態(tài)的模糊圖像復(fù)原問(wèn)題轉(zhuǎn)變?yōu)橐环N良態(tài)問(wèn)題,為運(yùn)動(dòng)模糊圖像復(fù)原提供了新的發(fā)展空間。同時(shí),受壓縮感知理論的啟發(fā),編碼曝光的隨機(jī)采樣方式有望以低幀率的采樣實(shí)現(xiàn)高速成像。本文以對(duì)編碼曝光技術(shù)的優(yōu)化研究為出發(fā)點(diǎn),從模糊圖像復(fù)原和高速成像兩個(gè)方面深入探討了如何在成像設(shè)備與拍攝場(chǎng)景之間存在大尺度相對(duì)運(yùn)動(dòng)的情況下獲取目標(biāo)清晰圖像的問(wèn)題。論文的主要?jiǎng)?chuàng)新點(diǎn)及取得的研究成果包括:(1)提出了一種基于勒讓德序列和遺傳算法的編碼曝光最優(yōu)碼字搜索方法。編碼曝光最優(yōu)碼字的搜索空間會(huì)隨著碼字長(zhǎng)度呈指數(shù)級(jí)增長(zhǎng),當(dāng)前的碼字搜索方法只能用于長(zhǎng)度較短碼字的搜索。本文將信息論領(lǐng)域中低互相關(guān)度的勒讓德序列用于編碼曝光成像中,通過(guò)對(duì)勒讓德序列進(jìn)行簡(jiǎn)單的旋轉(zhuǎn)和延拓操作進(jìn)一步提高了碼字的性能,得到了改進(jìn)勒讓德序列。將改進(jìn)勒讓德序列作為遺傳算法的初始種群,利用遺傳算法的交叉和變異算子實(shí)現(xiàn)了對(duì)改進(jìn)勒讓德序列的進(jìn)一步優(yōu)化,得到了編碼曝光最優(yōu)碼字。該碼字搜索方法可以很好地滿足編碼曝光技術(shù)對(duì)于碼字可逆性的要求,且能大大降低復(fù)原圖像的噪聲。由于該方法充分利用了勒讓德序列可以由公式快速計(jì)算得到的優(yōu)勢(shì),使得該方法效率很高,適合搜索長(zhǎng)度較長(zhǎng)的碼字。(2)提出了一種考慮CCD傳感器噪聲的編碼曝光最優(yōu)碼字搜索方法。編碼曝光模式下CCD傳感器噪聲比較嚴(yán)重,從實(shí)用化的角度出發(fā),在尋找最優(yōu)碼字時(shí)需要充分考慮傳感器噪聲的影響。本文首先基于仿射噪聲模型系統(tǒng)分析了編碼曝光相機(jī)的傳感器噪聲成分;其次給出了光子噪聲條件下最優(yōu)碼字結(jié)構(gòu)和復(fù)原圖像信噪比增益關(guān)系的解析表達(dá)式,并對(duì)真實(shí)的編碼曝光相機(jī)進(jìn)行了噪聲標(biāo)定;針對(duì)已有的碼字搜索方法多采用近似窮極搜索,時(shí)間效率低的缺點(diǎn),最后提出了考慮CCD噪聲的尋找最優(yōu)碼字的適應(yīng)度函數(shù),并采用遺傳算法搜索編碼曝光相機(jī)的最優(yōu)碼字。該算法不但提高了碼字搜索效率,并且大幅度地提高了復(fù)原圖像的信噪比。(3)提出了一種基于圖像能量譜統(tǒng)計(jì)信息分析的編碼曝光圖像模糊尺度自動(dòng)估計(jì)方法。編碼曝光圖像模糊信息是非連續(xù)的,使得當(dāng)前流行的模糊尺度估計(jì)方法失去效力。本文通過(guò)對(duì)編碼曝光模糊圖像能量譜統(tǒng)計(jì)數(shù)據(jù)進(jìn)行分析,發(fā)現(xiàn)復(fù)原圖像的能量譜統(tǒng)計(jì)數(shù)據(jù)點(diǎn)發(fā)散程度與圖像復(fù)原過(guò)程中輸入的模糊尺度的正確程度緊密相關(guān)。即只有使用正確的模糊尺度時(shí),經(jīng)過(guò)反卷積運(yùn)算后得到的復(fù)原圖像能量譜統(tǒng)計(jì)數(shù)據(jù)點(diǎn)的發(fā)散程度最小�；诖�,本文對(duì)圖像能量譜統(tǒng)計(jì)數(shù)據(jù)點(diǎn)進(jìn)行多項(xiàng)式擬合,用殘差平方和的大小來(lái)代表復(fù)原圖像能量譜統(tǒng)計(jì)數(shù)據(jù)點(diǎn)的發(fā)散程度。編碼曝光圖像的復(fù)原可以采用快速的直接反卷積算法,因此本文基于迭代尋優(yōu)的思路來(lái)估計(jì)編碼曝光模糊圖像的模糊尺度。給定一個(gè)初始的模糊尺度,使用全局搜索算法,則能快速地得到編碼曝光模糊圖像正確的模糊尺度。(4)提出了一種基于單個(gè)編碼曝光相機(jī)進(jìn)行高速視頻重建的方法。充分考慮到在現(xiàn)代傳感器設(shè)備上的易實(shí)現(xiàn)能力,進(jìn)一步探索了使用單個(gè)編碼曝光相機(jī)實(shí)現(xiàn)高速視頻幀重建的可能性�？紤]到高速視頻信號(hào)的空間冗余和時(shí)間冗余存在很大差別,本文提出使用克羅內(nèi)克積構(gòu)建三維雙曲線小波基來(lái)同時(shí)稀疏表示高速視頻信號(hào)的空間冗余和時(shí)間冗余�；诓煌叨鹊姆纸�,雙曲線小波基可以同時(shí)建模高速視頻各個(gè)維度上不同的信號(hào)結(jié)構(gòu),恰好迎合了高速視頻信號(hào)在空間維和時(shí)間維上具有不同平滑度的本質(zhì)屬性。為了進(jìn)一步提高重建視頻幀的質(zhì)量,本文充分利用了1?凸優(yōu)化模型可以進(jìn)一步融合先驗(yàn)知識(shí)的特性,在重建模型中加入高速視頻信號(hào)幀間相關(guān)性的全變分正則化項(xiàng),以進(jìn)一步建模視頻的時(shí)間冗余。最后通過(guò)最小化一個(gè)凸優(yōu)化問(wèn)題實(shí)現(xiàn)了從低幀率的編碼曝光圖像序列中重建出高質(zhì)量的高速視頻幀。
[Abstract]:Remote sensing imaging system is the need for a variety of information integration platform, imaging system of various bands were effectively integrated and unified, requirements of each system can provide enough accurate information sources. An important part of optical remote sensing imaging system based on UAVs as information integration, the image motion blur problem will affect the whole remote sensing imaging system the decision support ability. With the rapid development of UAV technology, remote sensing imaging system of UAV platform is playing an increasingly important role in the field of Remote Sensing Imagery Based on remote sensing system. Therefore, to solve the information integration in UAV remote sensing image motion blur problem has the urgent practical needs. The UAV remote sensing image motion blur is mainly composed of between the imaging device and the large scale scene caused by the relative motion. According to the motion blurred image, the main There are two solutions: one is image restoration algorithm using postprocessing method; the two is the use of high-speed imaging technology. However, traditional image restoration is an ill posed problem for large scale motion blurred image restoration effect is not ideal. The high-speed imaging technique requires special hardware support, price and application the scope is limited. In recent years, the development of a computational photography field exposure imaging encoding technology, creatively change fuzzy image restoration problem is a kind of morbid state and problems, provide new development space for the restoration of blurred image motion. At the same time, inspired by the theory of compressed sensing, random sampling method of encoding exposure is expected to in order to achieve high speed sampling of low frame rate imaging. This paper to study the optimization of the encoding lithography technology as the starting point, from the aspects of fuzzy image restoration and high-speed imaging of two is discussed How to get a clear image of target existence problem of large scale of relative motion between the imaging device and the filming of the scene. The main innovation points and research achievements include: (1) proposed a Legendre sequence and genetic algorithm encoding code word searching method based on optimal exposure exposure. The optimal codeword search space encoding as the codeword length grows exponentially, the searching method can only be used for short length codeword search. In this paper, information theory in the field of low cross-correlation sequence of Legendre encoding for exposure imaging, by simple rotation and extension operation to further improve the performance of the code on the Legendre sequence, improved Legendre the improved Legendre sequence. Sequence as the initial population of genetic algorithm, the improved Legens using crossover and mutation operator of genetic algorithm To further optimize the de sequence, obtained the optimal exposure. The encoding codeword searching method can well satisfy the encoding technology for the reversible exposure code requirements, and can reduce the noise image. The method makes full use of the Legendre sequence can be calculated by the formula of fast advantage, which makes the method efficiency high, suitable for search long codewords. (2) proposed an optimal exposure searching method of CCD sensor noise is considered. The exposure mode encoding encoding of CCD noise is more serious, from the practical angle, fully considering the influence of sensor noise need to search the optimal codeword. Based on affine noise model analysis of sensor noise component encoding exposure camera; then gives the optimal codeword structure conditions under photon noise and image SNR gain The analytical expression of interests, and the real encoding of noise exposure camera calibration; the searching method has more than one using approximate search time, low efficiency, and finally put forward the CCD noise is considered to find the optimal codeword fitness function, and genetic algorithm is adopted to search the optimal codeword encoding exposure camera. The algorithm not only improves the codeword search efficiency, and greatly improve the image SNR. (3) proposed a statistical information analysis of energy spectrum image encoding exposure image fuzzy scale automatic estimation method based on fuzzy information encoding. Exposure image is not continuous, the fuzzy scale current estimation method of losing effectiveness. Based on the analysis of fuzzy image encoding exposure energy spectrum data, found that the energy spectrum of the statistical data of image restoration and image point of divergence degree Closely related to the degree of fuzzy input scale correctly in the course of restoration. Only use fuzzy scale correctly, obtained by deconvolution restoration after image energy spectrum statistics point of divergence is minimized. Based on this, this paper fitting the image energy spectrum data, and the residual square size to represent the divergence the degree of image energy spectrum statistical data points. Encoding image restoration can be used direct exposure deconvolution algorithm is fast, so the iterative optimization method based on Fuzzy scale to estimate the exposure encoding fuzzy image. Given an initial fuzzy scale, using a global search algorithm, it can quickly get the correct exposure encoding fuzzy scale the blurred image. (4) proposed a single encoding method for high speed video camera exposure reconstruction based on fully considering the transfer in the modern. The sense of easy ability to achieve device on, to further explore the possibility of using a single encoding reconstruction high-speed video frame exposure camera. Considering the different spatial and temporal redundancies of high-speed video signal, the paper proposes using the Kronecker product line to construct three-dimensional hyperbolic wavelet and sparse representation of spatial redundancy and temporal redundancy of high-speed video signal based on the different decomposition scales. Wavelet basis can also signal, the hyperbolic structure of the various dimensions of different modeling of high speed video, just to meet the high speed video signal has a different nature smoothness in the space and time dimension. In order to further improve the quality of the reconstructed video frame, this paper makes full use of the 1 Characteristics of convex optimization model can be further? Incorporating prior knowledge into high speed video signal, the inter frame correlation in the reconstruction model of total variation regularization In order to further model the temporal redundancy of video, and finally minimize a convex optimization problem, a high quality video frame is reconstructed from the low frame rate encoded exposure image sequence.

【學(xué)位授予單位】：國(guó)防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TP751

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本文編號(hào)：1574887