本文關(guān)鍵詞： 空間遙感圖像壓縮 CCSDS算法 碼流分配 感興趣區(qū)域 itti模型　出處：《中國(guó)科學(xué)院研究生院(長(zhǎng)春光學(xué)精密機(jī)械與物理研究所)》2014年博士論文　論文類型：學(xué)位論文

【摘要】：隨著空間遙感技術(shù)的發(fā)展，光學(xué)遙感圖像分辨率越來(lái)越高，單位時(shí)間內(nèi)獲得的圖像數(shù)據(jù)量越來(lái)越大。然而，空間遙感圖像的傳輸和存儲(chǔ)技術(shù)發(fā)展相對(duì)遲緩。因此，獲得圖像后，有必要對(duì)圖像進(jìn)行壓縮編碼處理。對(duì)于一幅圖像而言，我們通常只關(guān)注其中的一部分區(qū)域或目標(biāo)，即感興趣區(qū)域，而其他區(qū)域稱為背景區(qū)域。所以，在對(duì)圖像進(jìn)行壓縮處理時(shí)，可以采用感興趣區(qū)域壓縮算法：對(duì)感興趣區(qū)域進(jìn)行無(wú)損壓縮或低壓縮比壓縮，而對(duì)背景區(qū)域采用大壓縮比壓縮，從而既降低了圖像傳輸對(duì)帶寬的要求，又減少了感興趣區(qū)域細(xì)節(jié)信息的丟失。論文主要研究一種基于CCSDS的空間遙感圖像感興趣區(qū)域壓縮算法，并嘗試采用基于視覺(jué)注意機(jī)制的itti模型來(lái)檢測(cè)圖像的感興趣區(qū)域。 論文以海洋監(jiān)視衛(wèi)星圖像為研究對(duì)象，嘗試采用itti模型來(lái)檢測(cè)圖像內(nèi)的艦船目標(biāo)等感興趣區(qū)域。首先，研究了itti模型的算法處理過(guò)程：分析圖像的多種特征，并將其融合生成特征顯著圖；然后采用勝者為王和返回抑制機(jī)制提取出視覺(jué)注意點(diǎn)；最后以該點(diǎn)為圓心，設(shè)置固定值為半徑，劃定圓形區(qū)域?yàn)轱@著區(qū)域。本文將視覺(jué)注意點(diǎn)的提取轉(zhuǎn)移過(guò)程建立為電容陣列充電模型，并在算法中引入了離散矩變換，增強(qiáng)了圖像紋理特征響應(yīng)；由視覺(jué)注意點(diǎn)提取顯著目標(biāo)時(shí)，本文采用了閾值分割算法。實(shí)驗(yàn)結(jié)果表明，改進(jìn)算法所提取的顯著區(qū)域形狀大小基本與目標(biāo)一致，且顯著區(qū)域包含背景少。與itti模型相比，改進(jìn)算法更適合應(yīng)用于海洋監(jiān)視衛(wèi)星圖像艦船目標(biāo)檢測(cè)提取。 本文探討了SPIHT、JPEG2000以及CCSDS等圖像壓縮算法，并重點(diǎn)研究了CCSDS壓縮標(biāo)準(zhǔn)。CCSDS將圖像分為若干個(gè)不同的段，段與段之間獨(dú)立編碼，每段的紋理復(fù)雜度不同，所包含的信息量不同。本文采用梯度來(lái)衡量圖像的紋理復(fù)雜度，，并據(jù)此提出了一種基于梯度的壓縮碼流控制算法，紋理越復(fù)雜的段，所分配的碼流容量越大，紋理越簡(jiǎn)單的段，所分配的碼流容量越小。實(shí)驗(yàn)結(jié)果表明，采用該碼流控制算法以后，恢復(fù)圖像的信噪比有所改進(jìn)。 本文根據(jù)CCSDS的壓縮特點(diǎn)，提出了一種新的感興趣區(qū)域壓縮算法，將感興趣區(qū)域和背景區(qū)域進(jìn)行分割，分別作為兩幅獨(dú)立的圖像進(jìn)行壓縮。在壓縮前，首先將感興趣區(qū)域掩膜編碼，然后將碼流按一定比例分配給感興趣區(qū)域和背景區(qū)域。之后引入基于梯度的碼流分配算法，依次對(duì)感興趣區(qū)域和背景區(qū)域編碼，從而實(shí)現(xiàn)基于CCSDS的感興趣區(qū)域圖像壓縮。實(shí)驗(yàn)結(jié)果表明，該算法能夠提高圖像感興趣區(qū)域的恢復(fù)效果。
[Abstract]:With the development of space remote sensing technology, the resolution of optical remote sensing image is getting higher and higher, and the amount of image data per unit time is getting larger and larger. However, the transmission and storage technology of space remote sensing image is relatively slow. It is necessary to compress and encode the image. For an image, we usually focus on only a part of the region or target, that is, the region of interest, while the other region is called the background region. So, when we compress the image, we usually focus on the region of interest. The region of interest compression algorithm can be used: lossless compression or low compression ratio compression for the region of interest, and large compression ratio compression for the background region, which not only reduces the bandwidth requirement of image transmission, but also reduces the bandwidth requirement of image transmission. This paper mainly studies a region of interest compression algorithm based on CCSDS, and tries to use the itti model based on visual attention mechanism to detect the region of interest. In this paper, the marine surveillance satellite image is taken as the research object, and the itti model is used to detect the region of interest such as the ship target in the image. Firstly, the algorithm processing process of the itti model is studied: analyzing the various features of the image. The feature salient map is generated by fusion, and then the visual attention point is extracted by the winner king and the return inhibition mechanism. Finally, the center of the point is set as the fixed value and the radius is set. In this paper, the extraction and transfer process of visual attention points is established as a capacitive array charging model, and the discrete moment transform is introduced into the algorithm to enhance the texture feature response of the image. In this paper, the threshold segmentation algorithm is used to extract salient objects from visual attention points. The experimental results show that the shape of significant regions extracted by the improved algorithm is basically the same as that of the target, and the significant regions contain less background. Compared with the itti model, The improved algorithm is more suitable for ship target detection and extraction from marine surveillance satellite images. In this paper, we discuss the image compression algorithms such as SPIHT JPEG2000 and CCSDS, and focus on the research of CCSDS compression standard .CCSDs divide the image into several different segments, and each segment has different texture complexity. In this paper, gradient is used to measure the texture complexity of the image, and a gradient-based compressed bitstream control algorithm is proposed. The more complex the texture, the larger the capacity of the allocated bitstream and the simpler the texture. Experimental results show that the SNR of the restored image can be improved by using the bitstream control algorithm. In this paper, according to the characteristics of CCSDS compression, a new region of interest compression algorithm is proposed. The region of interest and the background region are segmented as two independent images. Firstly, the region of interest is masked, then the code stream is allocated to the region of interest and the background region according to a certain proportion. Then, a gradient-based bitstream allocation algorithm is introduced to code the region of interest and the background region in turn. The experimental results show that the proposed algorithm can improve the restoration effect of the region of interest.
【學(xué)位授予單位】：中國(guó)科學(xué)院研究生院(長(zhǎng)春光學(xué)精密機(jī)械與物理研究所)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP751

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