【摘要】：圖像拼接是將多個(gè)具有一定重疊度的攝影圖像序列合成為全景的高分辨率圖像的過程。圖像拼接目前被廣泛使用在諸多應(yīng)用領(lǐng)域，如醫(yī)學(xué)成像、視頻拼接、數(shù)字地圖和衛(wèi)星照片的拼接、遙感圖像拼接等。圖像拼接一般由圖像匹配、圖像配準(zhǔn)、圖像融合幾個(gè)主要步驟組成。 隨著國內(nèi)外對無人機(jī)的應(yīng)用日益廣泛，如何快速處理無人機(jī)獲取的大量遙感圖像數(shù)據(jù)已經(jīng)成為一項(xiàng)十分重要的研究內(nèi)容，其中主要以無人機(jī)圖像的拼接最受關(guān)注。其原因在于，遙感圖像在多個(gè)領(lǐng)域內(nèi)都有重要的作用。比如應(yīng)急救援、電力線路巡查、地圖制圖等，因此，如何將所獲取的大量遙感圖像進(jìn)行合并，以獲取拼接后整個(gè)拍攝場景的圖像在各個(gè)方面均有較高的應(yīng)用需求。然而，在遙感圖像拼接過程中，由于拍攝角度不同及光照明暗變化等原因，導(dǎo)致拼接后的圖像會出現(xiàn)明顯的拼接縫現(xiàn)象。又因圖像兩兩間重疊度較大，對重疊區(qū)域進(jìn)行融合的階段所需時(shí)間較長。因此，對遙感圖像重疊區(qū)域進(jìn)行融合的算法在整個(gè)拼接過程中尤為重要。 本文首先對圖像拼接基本流程中的主要步驟及其所涉及的相關(guān)技術(shù)進(jìn)行了概括總結(jié)，然后，綜合考慮遙感圖像序列的特點(diǎn)實(shí)現(xiàn)了本文中所介紹的遙感圖像序列拼接方法，并在此基礎(chǔ)上總結(jié)了原有圖像融合算法的一些缺點(diǎn)，從而提出一種新的遙感圖像加權(quán)融合算法，該算法對原融合算法存在的問題進(jìn)行了改進(jìn)。算法能夠漸進(jìn)的對遙感圖像重疊區(qū)域進(jìn)行融合，較好的消除了光照明暗的影響，實(shí)現(xiàn)了遙感圖像的無縫拼接，使拼接效果有較好的提升。 最后，在對圖像重疊區(qū)域進(jìn)行融合的過程中，，取待拼接原圖像中坐標(biāo)點(diǎn)處的像素值時(shí)需在基準(zhǔn)圖像坐標(biāo)系中將像素坐標(biāo)進(jìn)行逆變換從而確定某一坐標(biāo)對應(yīng)原圖像中的坐標(biāo)值。由于遙感圖像分辨率較高，因此，按像素坐標(biāo)對所有像素點(diǎn)進(jìn)行坐標(biāo)逆變換所消耗的時(shí)間較多，導(dǎo)致融合拼接速率較慢。文中改進(jìn)的融合算法考慮到對像素坐標(biāo)逆變換的并行性，利用GPU并行加速技術(shù)對遙感圖像融合拼接期間的像素坐標(biāo)逆變換過程進(jìn)行并行處理從而提高融合拼接效率、優(yōu)化算法性能，最終通過實(shí)驗(yàn)證明了該算法的有效性。
[Abstract]:Image mosaic is the process of synthesizing multiple sequences of photographic images with certain overlap into panoramic high resolution images. Image mosaic is widely used in many applications, such as medical imaging, video mosaic, digital map and satellite image mosaic, remote sensing image mosaic and so on. Image stitching consists of image matching, image registration and image fusion. With the increasing application of UAV at home and abroad, how to quickly process a large number of remote sensing image data obtained by UAV has become a very important research content, in which the most attention is paid to the image mosaic of UAV. The reason is that remote sensing images play an important role in many fields. Such as emergency rescue, power line inspection, map mapping, so how to obtain a large number of remote sensing images are merged to obtain the image of the whole scene after stitching has a higher application demand in all aspects. However, in the process of remote sensing image stitching, because of different shooting angle and the change of illumination and shade, the stitching will appear obviously. Because of the large overlap between the two images, it takes a long time to fuse the overlapped regions. Therefore, the fusion algorithm for overlapped regions of remote sensing images is particularly important in the whole mosaic process. In this paper, the main steps in the basic process of image stitching and the related technologies are summarized. Then, considering the characteristics of remote sensing image sequence, the method of remote sensing image sequence mosaic is realized. On this basis, some shortcomings of the original image fusion algorithm are summarized, and a new weighted remote sensing image fusion algorithm is proposed, which improves the existing problems of the original fusion algorithm. The algorithm can gradually fuse the overlapped region of remote sensing image, eliminate the influence of light and dark, realize the seamless stitching of remote sensing image, and improve the effect of remote sensing image. Finally, in the process of image overlapping region fusion, when the pixel value of coordinate point in the original image is to be stitched, the pixel coordinate should be inversely transformed in the reference image coordinate system to determine the coordinate value corresponding to a certain coordinate in the original image. Because of the high resolution of remote sensing images, it takes more time to invert all pixels according to pixel coordinates, resulting in a slow fusion rate. Considering the parallelism of inverse transformation of pixel coordinates, the improved fusion algorithm uses GPU parallel acceleration technology to parallel process the inverse transformation of pixel coordinates during remote sensing image fusion and stitching, so as to improve the efficiency of fusion and stitching. The performance of the algorithm is optimized and the effectiveness of the algorithm is proved by experiments.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TP751

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