為了減少儲存資訊量和網路傳輸的負載，影像壓縮已被廣泛的應用在多媒體通訊上，然而在壓縮的過程中，影像的邊緣附近產生震盪型式的雜訊，這個稱為環效應。許多去除環效應所提出的演算法都沒有考慮到更小的區域性去環效應問題，不但把影像大量使用掃描線都儲存起來作為其後處理使用，而且那些方法在去除環效應同時沒有保留影像的細節和紋理。本論文提出一個改善的演算法，在儲存影像更少量掃描線的情況下進行環效應偵測以保留影像細節和紋理，更進一步在邊緣區域使用濾波和使用邊緣區域資訊去保留紋理區域。實驗結果說明了我們所提出的演算法可以準確偵測出環效應的區域，而去環效應的結果在主觀的畫質和客觀的數據上都比起其他方法有改善。

Data compression is commonly used to reduce the data storage and transmission costs in multimedia communication. However, compression introduces the spurious oscillations known as ringing artifacts near the major edges of objects. Many algorithms were proposed to solve this problem without considering a fewer local processing, not only a large number of memory rows are loaded into the buffer for post-processing but also fail to preserve image details and image texture while removing ringing artifacts simultaneously. In this thesis, we propose an improved algorithm to detect ringing artifacts with less memory rows and to preserve image details and textures. Moreover, the potential edge region will be filtered and the texture region will be preserved by using the local information of its. Simulation results show that the proposed the algorithm can accurately detect the ringing artifact occurred on the decompressed image. By comparing other methods, the better objective performance of our method can be achieved. Subjectively, the visual quality of surpass that of the comparative algorithms.

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