數位影像總是在生活中扮演著重要的角色,因此許多的視訊處理標準便成為熱門的研究主題,並促使影像處理的技術日趨進步,與MPEG-1、MPEG-2、H.263、MPEG-4和H.264/AVC等多媒體技術相對地快速演進,尤其MPEG-4和H.264/AVC更是近來常被討論的一種標準。 高清晰度數位電視(HDTV)大多使用MPEG-4或H.264的壓縮技術,但是當增加壓縮率時,影像就會出現不自然的邊緣,這稱為方格效應,本論文將探討MPEG-4或H.264的去區塊效應(De-blocking)演算法,此演算法獨立於各種影像技術解碼後的影像,因此我們將採用這高效率De-blocking演算法作實驗證明,而此演算法乃分析一個像素點強度趨勢與橫跨兩區塊邊緣的強度,比較像素點在區塊內的活動,並且不同的濾波器強度可以去除區塊效應。然後,我們在De-blocking演算法之後增加了影像銳化之演算法,提高影像的邊緣,並希望可以改善區塊之間糢糊不清楚的影像。根據論文實驗結果,我們提出的方法可改善影像的區塊效應,並可藉由客觀的PSNR值發現影像品質的提升。
In our daily life, digital image is always an important part for us. Moreover many standards of video coding become popular research topics, like MPEG-1, MPEG-2, H.263, MPEG-4 and H.264/AVC etc. It has great impact on video quality. Especially, MPEG-4 and H.264/AVC has been paid most attention recently. Most high definition televisions (HDTV) use MPEG or H.264 compression standard to compress the video data. When we increase the compression rate for huge amount of video stream, the block-based compression methods will generate unnatural edges between block's boundaries. This is called blocking effect or blocking artifact. In this thesis, a de-blocking algorithm to improve the blocking effect is proposed. The metric estimates block grid by analyzing the discontinuity of a pixel intensity trend across the block edge and by comparing it against pixel activities. And filtering strengths can smooth out the blocking artifacts. According to the experimental results, the proposed method demostrates better performance than those de-blocking methods by H.26L and MPEG-4 in terms of PSNR. Noticeable perceptual improvements of image quality are achievable.
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