Abstract
본 논문에서는 커브형 집적영상 시스템에서 부분적으로 가려진 먼 거리 3차원 물체의 인식 향상을 위한 새로운 direct pixel-mapping (DPM)방법을 제안한다. 제안 방법은 커브형 집적영상 시스템에서 DPM 방법에 의해 먼 거리에 위치한 3차원 물체로부터 픽업된 요소영상배열 (elemental image array, EIA)은 가시적으로 가까운 거리에서 픽업한 것과 같은 새로운 요소영상배열을 생성한다. 이러한 특성은 재생한 3차원 물체 영상의 해상도를 향상 시킬 수 있고, 이로 인하여 먼 거리에 위치한 3차원 물체에 대한 인식 성능을 향상 시킬 수 있다. 컴퓨터적 실험결과와 기존 방법과의 비교를 통하여 제안방법으로 재생한 물체의 PSNR과 NCC의 값이 평균 1.75dB와 4.56% 향상됨을 확인할 수 있었다. In this paper, we propose a novel approach to enhance the recognition performance of a far and partially occluded three-dimensional (3-D) target in computational curving-effective integral imaging (CEII) by using the direct pixel-mapping (DPM) method. With this scheme, the elemental image array (EIA) originally picked up from a far and partially occluded 3-D target can be converted into a new EIA just like the one virtually picked up from a target located close to the lenslet array. Due to this characteristic of DPM, resolution and quality of the reconstructed target image can be highly enhanced, which results in a significant improvement of recognition performance of a far 3-D object. Experimental results reveal that image quality of the reconstructed target image and object recognition performance of the proposed system have been improved by 1.75 dB and 4.56% on the average in PSNR (peak-to-peak signal-to-noise ratio) and NCC (normalized correlation coefficient), respectively, compared to the conventional system.
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