近年來，影像解析度放大已成為一個熱門的研究議題，其主要目的為：藉由低
解析度影像來產生高解析度影像，而這些高解析度影像必須看起來就像原本即由一個高解析度的相機所取得，或者至少呈現較自然的紋理細節。此一技術又稱為超解析，目前廣泛被應用在高品質數位電視、智慧型手機、衛星影像、監視系統攝影機等設備上。而一般常見的影像放大演算法，空間域上以內插為基礎的方法可能有過度模糊或是鋸齒狀等不好的現象，而小波域上的影像放大方法則有可能產生震鈴現象。在本論文中，提出一個針對放大後影像之邊緣增強演算法，有效減少影像放大後邊緣鋸齒狀現象，並使影像邊緣看起來較清楚、自然。實驗結果顯示，我們的演算法在提供較好的影像的視覺品質的同時，亦有良好的峰值信噪比。

Image upscaling has recently become a hot research topic. The main purpose of image upscaling is to obtain high-resolution images from low-resolution ones and these upscaled images should look like they had been taken with a camera having the resolution the same as upscaled images, and at least, present natural textures. This technique is also known as super-resolution which had been widely used in high definition televisions, smart phones, satellite images, and surveillance cameras. In spatial domain, interpolation-based methods might meet defects such as blurring and jagged artifact. However, the upscaling methods in wavelet domain might fall into ringing artifact. In this thesis, we propose an edge enhancement method for upscaled images which is able to suppress the jagged artifact effectively, and it also provides more natural and clearer edges. The experimental results show that our algorithm provides better subjective visual qualities, and meanwhile, the peak signal-to-noise ratio(PSNR) is still good.

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