| Summary: | 碩士 === 國立交通大學 === 電子研究所 === 98 === Disparity estimation is one of the critical elements in a 3D video processing system. Many techniques have been proposed to calculate the disparity map from a pair of images and the graph cut (GC) algorithm is one of the recognized better disparity estimation schemes. However, GC has a very high computational complexity.
In this thesis, we propose a fast GC algorithm for disparity estimation purpose. Two accelerating techniques are suggested: one is the early termination rule and the other is prioritizing the α-β swap pair search order. Our simulations show that the proposed fast GC algorithm can reduce 68% computing time on the average, when compared with the original GC scheme. Meanwhile, its disparity estimation performance is about the same as that of the original GC.
Another speed-up technique we adopt is the multi-resolution approach. The original images are down-sampled and a low-resolution disparity map is first estimated. Then, the low-resolution disparity map is up-sampled as the initial values for estimating the disparity map of the original images. Several down-sampling and up-sampling filters are tested to find the best combination. Our simulation shows that the multi-resolution GC (MRGC) algorithm uses only 16% of the original computing time and the bad pixel probability increases only by 1%. The last topic we investigate is disparity estimation using multi-camera pictures. The initial exploration shows some interesting results. Further investigation is needed to fully take the advantage of multiple images recoded by a camera array.
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