Panoramic of Image Reconstruction Based on Geospatial Data using SIFT (Scale Invariant Feature Transform)

Reconstruction can mean the return of something in its place of origin, rearrangement of existing material and rearranged as it is or the original event. Where in this study used the SIFT, match and homography method. Based on the results of this experiment, it was able to reconstruct panoramic images. After the stitching process on geospatial data found was a problem where the GPS data is lost and the results are still there overlap. Where the initial data has GPS data.From the experimental results, we have reconstructed the panoramic data based on geospatial data using SIFT (Scale Invariant Feature Transform) method, in which the key point results obtained by matching the original image and stitched image. It can be seen from key point results from four images namely image A = 7, image B = 16, image C = 27 and image D = 32. By summing the key points from those images, the total number of key points are 82. The average of key points will be 20.5 and the average of the run time of the program is 0.0385 second. By knowing the position of initial image coordinate on the stitched image, we know where the position of longitude and latitude is. The stitched image from an image A located in (7⁰, 16′, 51.2675″S/112⁰, 47′, 32.1102″E), image B located in (7⁰, 16′, 51.4336″S/112⁰, 47′, 32.2728″E), image C located in (7⁰, 16′, 51.6024″S/112⁰, 47′, 32.3975″E) and image D located in (7⁰, 16′, 51, 8191″S/112⁰, 47′, 32.5617″E). Meanwhile, GPS coordinates point in image A lies in x, y = (205, 164) and x ′, y′ = (603.15), in image B lies in x, y = (194, 175) and x ′, y′ = (598.70), image C located in x, y = (196, 110) and x ′, y′ = (599.71) and image D located in x, y = (28, 110) and x ′, y′ = (607, 130).