本研究發展了一套可攜式全景影像測繪系統(Portable Panoramic Image Mapping System, PPIMS)，本系統針對車載之測繪系統無法進入之地區所設計，例如崎嶇地形、森林地區等等。PPIMS是以一個特製的平台裝載了八台相機和一個GPS接收儀，可以同時拍攝八張影像，並以e-GPS系統來定位。而利用此系統以多測站獲取影像時，會產生大量的影像，在處理及量測這些影像時，使用者難以尋找目標影像，影像的量度工作相當容易混淆或困惑。
本文提出一個以環景影像進行攝影測量的新概念，不但突破傳統攝影測量之有限的FOV，也解決了PPIMS影像過多容易混淆的問題。以本系統拍攝的八張影像形成球形環景影像(spherical panorama image, SPI)，而以此球形環景影像取代原本的影像，應用於攝影測量和製圖，由於此SPI並不完全符合共線條件，造成在相鄰影像重疊處的拼接錯位。本文首先提出多測站SPI的光束法平差，以解算測站平台方位及共軛點物空間坐標，而由於SPI不符合嚴謹共線幾何，固此亦然對此缺失提出以所求得的物點坐標來修正SPI不完美的幾何，再重新解算測站平台方位及共軛點物空間坐標，直至收斂。

針對球形環景影像的光束法平差，我們做了兩個實驗，兩者皆經過檢核點的驗證，其中一個實驗地點在成大自強校區的測試場，另一個在地景較為複雜的億載金城。應用球形環景影像的改正於光束法平差後，在自強校區的測試場的實驗成果顯示出RMSD在三個方向都有顯著性的降低，其從(±0.321m, ±0.741m, ±0386m)降低至(±0.209m, ±0.376m, ±0.270m)，而在億載金城的實驗成果則顯示出RMSD在三個方向變得更為一致，約為0.1m。兩個實驗都證實了以球形環景影像來進行光束法平差是可行的，而應用球形環景影像的改正於光束法平差是必須而且有效的。

為了瞭解使用球形環景影像和原始影像的實際差異，我們也對兩者做了比較，在自強校區的測試場之實驗中，最大的旋轉角差值約為0.03°，而檢核點在忽略兩個不可靠的點後，最大的坐標差值約為0.06m，在億載金城之實驗中，最大的旋轉角差值約為0.03°， 而全部檢核點的坐標差值皆小於0.04m。
上述證實了這兩個實驗使用球形環景影像和使用原始影像的成果是一致的，這也代表球形環景影像是可以取代原始影像於光束法平差。

In this study, we developed a portable panoramic image mapping system (PPIMS). It is designed for some areas that vehicle-based mapping systems are not allowed to enter, such as rugged terrains, forest areas, and etc. PPIMS is a specially designed platform equipped with eight cameras and a GPS receiver that it can capture eight images simultaneously with e-GPS positioning. When images are taken from multiple stations, a large amount of images are needed to handle and measure. Finding targets among images becomes a puzzled task.
This study proposes a new concept of photogrammetry by using panoramic images. It not only breaks the limitation of FOV in traditional photogrammetry but also resolves the problem that handling a lot of images are confusing. Eight images captured with PPIMS can form an spherical panorama image (SPI), which is called PPIMS SPI. The PPIMS SPIs are then used for photogrammetric triangulation and mapping instead of using the original images. Because the collinearity condition is not rigorously kept that causes the gaps on the cutting edges of overlapped images. This study first proposes using SPIs in bundle adjustment to solve the orientation of stations and coordinates of conjugate points in the object space. Then we aim at the deficiency of PPIMS SPI to fix the imperfect geometry of PPIMS SPIs by coordinates of object points solved. And solve the orientation of stations and coordinates of conjugate points in the object space again until the convergence.

Two experiments using PPIMS SPIs for bundle adjustment are done, and both their results are validated with check points. One is on the test field in Tzu-Chiang Campus, and another one is in the Eternal Golden Castle (EGC), which has the much complicated landscape. On the test field in Tzu-Chiang Campus, the RMSD values in three directions decreases significantly from (±0.321m, ±0.741m, ±0386m) to (±0.209m, ±0.376m, ±0.270m) after applying corrections for PPIMS SPIs. In EGC project, the RMSD values in three directions become consistent and are about 0.1 m after applying corrections for PPIMS SPIs. Both of them confirm bundle adjustment of SPI is possible, and applying corrections for PPIMS SPIs is necessary and effective for bundle adjustment.

We also compare the results using SPIs with original images to understand their real differences. On the test field in Tzu-Chiang Campus, the maximum difference of rotation angles is about 0.03 degrees. Ignoring two unreliable check points, the maximum difference of check point coordinates is about 0.06 meters. In EGC project, the maximum difference of rotation angles is about 0.03 degrees, and all difference of check point coordinates are under 0.04 meters.
The above confirms both results using SPIs are consistent with original images, that presents SPIs can replace original images in bundle adjustment.

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