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  • 學位論文

超解析度演算法使用於像機模組

Super resolution for Camera Module

指導教授 : 傅楸善

摘要


最近數位相機的使用是越來越普遍了, 而且也有越來越多人擁有具有相機功能的可攜式裝置, 如照相手機、個人數位助理、等等諸如此類設備。每個人都希望可以隨時為回憶留下照片記念。但是並不是每個人都可以擁有很好的相機功能, 所以拍出來的影像品質都不太好。因此我們需要一個強健性的超解析度演算法去重建回一張較高解析度的影像, 所以我們將介紹我們的方法去處理不同影像運動情況。但是在真實的情況可能會遭受不同的狀況, 例如相機本身快門速度的限制, 像機拍攝時的穩定度, 或是過快的移動物體…等等都會造成影像品質的下降。所以在我們的方法中將會專注在超解析度演算法中最重要的運動估計部份。 方法中將採用影像相減的作法去進行運動的估計。因此我們能找到一個精確的運動範圍去產生比較好的結果。

關鍵字

超解析度 相機模組

並列摘要


Recently, digital still cameras are very popular, and many people have portable devices with camera module such as camera phone, PDA, and other devices. Each of them usually wants to take a picture for remembrance at any time. But some of their images have poor quality. Therefore we need a robust algorithm to reconstruct a high-resolution image, so we will introduce our method to conquer different image motion situations. But in real scene, super-resolution algorithm may suffer many difficulties such as camera shutter speed limitation, image jitter, fast motion objects, and so on. Because above situations will result in reduced image quality, we will focus on motion estimation which is the most important part in super-resolution algorithm. We propose an alternate approach using image subtraction method to estimate motion objects. Therefore we can find accurate object motion range to get a better result.

並列關鍵字

Super Resoution Camera Module

參考文獻


[1] D. I. Barnea and H. F. Silverman, “A Class of Algorithms for Fast Image Registration,” IEEE Transactions on Computers, Vol. 21, No. 2, pp. 179-186, 1972.
[2] C. Y. Chen, Y. C. Kuo, and C. S. Fuh, “Image Reconstruction with Improved Super-Resolution Algorithm,” International Journal of Pattern Recognition and Artificial Intelligence, Vol. 18, No. 8, pp. 1513-1528, 2004.
[7] M. Irani and S. Peleg, “Improving Resolution by Image Registration,” CVGIP: Graphical Models and Image Proc., Vol. 53, pp. 21-249, 1991.
[8] A. Zomet, A. Rav-Acha, and S. Peleg, “Robust Super-resolution,” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, Vol. 1, pp. 645–650, 2001.
[3] M. Degroot, Optimal Statistical Decisions, McGraw-Hill, New York, 1970.

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