在影像相關應用領域中，高解析度的影像可提供影像的細節資訊，呈現出較接近真實的影像品質，滿足人眼視覺的感官需求。因此，利用超解析度影像重建技術取得高解析度影像成為影像處理中一項重要的研究議題。傳統的影像放大方法只能使用內插法放大單一影像，重建出的影像品質有限。多張影像超解析度影像重建方法利用多張低解析度影像重建出一張高解析度影像，可參考的資訊增加，重建影像的品質也隨之提升。
本論文提出了基於非均勻內插法的超解析度影像重建方法，分為三大步驟，第一步利用影像定位方法估測多張低解析度影像之間的次像素位移關係。第二步依據低解析度影像間的位移資訊，使用非均勻內插法內插出高解析度影像。為了提升影像品質，額外參考了影像中邊緣的資訊，盡量保留影像邊緣的部分，使視覺效果更銳利。第三步以盲目去迴旋積演算法完成影像復原，在系統模糊函數未知的情況下，去除系統雜訊與模糊效應，最終得到品質優良的高解析度影像。實驗結果顯示，與其他已知的研究相比，本論文所提出的方法提升了重建高解析度影像的品質，在主觀視覺感受與客觀數據評估上的表現都優於其他的演算法。

In many image processing applications, images with high resolution can provide more detailed information, and make images look close to the original scene. In order to satisfy human visual sense, using super-resolution image reconstruction technique to acquire a high-resolution image becomes an important research issue in image processing. Traditionally, image enlargement methods can only enlarge single image by interpolation. Thus, the quality of reconstructed image is constrained. Multiframe image super-resolution reconstruction approach is to obtain a high-resolution image using multiple low-resolution images. Therefore, there is more information that can be used to improve the image quality.
In this thesis, a super-resolution image reconstruction technique based on nonuniform interpolation method is proposed. This method consists of three major steps. First, the relative sub-pixel shifts between the multiple low-resolution images are estimated by image registration. Second, high-resolution image is reconstructed using an edge-oriented nonuniform interpolation method, which considers the edge information for image sharpness. Finally, blind deconvolution is used as image restoration process to remove blur and noise of the image since the system blur function is unknown. Experimental results show that the performance of the proposed method is better than that of other super- resolution approaches in terms of the subjective image quality and objective assessment.

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