그림 1. 360 VR 영상 합성 개념도 Fig. 1. Concept of the 360 VR image composition system
그림 2. 360 VR 영상 합성 과정 Fig. 2. Flowchart of the 360 VR image composition algorithm
그림 3. Gain-based 노출 보상 Fig. 3. Gain-based illuminance compensation
그림 4. Block gain-based 노출 보상 Fig. 4. Block gain-based illuminance compensation
그림 5. Gain-based 노출보상과 Block Gain-based 노출보상의 성능 비교 Fig. 5. Comparison between Gain-based compensation and Block Gain-based compensation algorithms. (a) Stitching without illumination compensation, (b) Stitched image with Gain-based illumination compensation algorithm, (c) Stitched image with Block Gain-based illumination compensation algorithm
그림 6. 장애물(손)의 유무에 따른 밝기 변화 Fig. 6. Change of brightness according to obstacle (hand)
그림 7. 카메라 촬영 방향에 따른 영상들 비교 Fig. 7. Pictures according to the direction of the camera
그림 8. 제안하는 알고리즘의 구성도 Fig. 8. The flowchart of the proposed algorithm
그림 9. 다양한 노출보상 알고리즘들을 이용한 스티칭 영상 Fig. 9. The stitched images resulted from the various compensation algorithms
그림 10. 그림 11의 입력 영상 Fig. 10. Input images for Fig 11
그림 11. 다른 색상의 입력 이미지들을 이용해서 스티칭한 영상들 Fig. 11. The stitched images resulted from the various compensation algorithms with input images having the different colors, (a) The image stitched by Gain-based compensation, (b) The image stitched by Block Gain-based compensation, (c) The image stitched by the proposed
그림 12. 다른 색상의 입력 이미지들을 이용해서 스티칭한 영상들 (복도) Fig. 12. The stitched images (hallway) resulted from the various compensation algorithms with input images having the different colors, (a) The image stitched by Gain-based compensation, (b) The image stitched by Block Gain-based compensation, (c) The image stitched by the proposed compensatoin algorithm
그림 13. 그림 14의 입력 영상 Fig. 13. Input images for Fig 14
그림 14. 급격하게 밝기가 변하는 입력 영상을 스티칭한 결과 Fig. 14. The stitched images resulted from the various compensation algorithms with input images having the different brightness, (a) The image stitched by Gain-based compensation, (b) The image stitched by Block Gain-based compensation, (c) The image stitched by the proposed compensatoin algorithm
그림 15. 밝기와 색상 보정이 모두 필요한 영상의 스티칭 결과 Fig. 15. The stitched images resulted from the various compensation algorithms with input images having the different brightness and color, (a) The image stitched by no compensation, (b) The image stitched by only color compensation, (c) The image stitched by only brightness compensation, (d)The image stitched by the proposed compensatoin algorithm
그림 16. 수평의 360도 파노라마 Fig. 16. Horizontality 360 degree panorama
그림 17. 밝기와 색상이 유사한 영상들의 스티칭 영상들 Fig. 17. The stitched images resulted from the various compensation algorithms with input images having the similar colors and brightness
표 1. 비슷한 사진들의 평균 밝기값 및 삼원색 구성 비율 비교 Table 1. Comparison of the averaged brightness and three primary colors in similar pictures
표 2. 기존 노출보상 기법들과 제안하는 노출보상 기법의 실행시간 비교 Table 2. Comparison between run times of Gain-based compensation, Block Gain-based compensation, and the proposed compensation al-gorithms
표 3. Fig 11의 0번째 영상과 4번째 영상의 오버랩 영역의 평균 밝기와 색상 비율 비교 Table 3. Comparison of the averaged brightness and three primary colors in the overlap region between image0 and image4 of Fig 11
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