隨著科技的發展顯示器的使用越來越普遍，並且可以和各種設備做緊密結合，例如手機，多媒體播放器等，因此配合不同大小螢幕的影像縮放技術越來越受重視，傳統的剪裁和非等比例縮放容易造成影像的變形或失真。Avidan and Shamir提出了一個影像細縫裁減(seam carving)，其依據影像內容來對影像重新調整大小的方法，被認為是一個有效的解決方法，使用簡單的濾波器來找出影像中高能量的區域並保留下來，但是很多時候這種演算法並不能產生令人滿意地結果，它無法應付各種類型的影像，例如有複雜背景或是高反差顏色的影像。本篇論文希望能夠對seam carving 演算法作改進，透過改變能量圖的計算方式，來降低複雜背景的高頻雜訊，使得在各種複雜背景的影像都能夠達到使用者期望的結果。 As displays become commonly used and are incorporated into more and more devices, such as mobile phones, multimedia players, there has been an increased focus on image resizing techniques to fill an image to an arbitrary screen size. Traditional methods such as cropping or scaling might introduce undesirable losses in information or distortion in perception. Recently, content-aware image retargeting method proposed by Avidan and Shamir called “Seam Carving” has good results. In particular, seam carving has gained attention as an effective solution, using simple filters to detect and preserve the high-energy areas of an image. But in some cases this algorithm may not provide satisfactory results, especially, for images having complex background or high-contrast colors. In this study, we would like to improve the existing seam carving methods by selecting more appropriate seams to remove so that it can adapt a variety of environment to provide desired results for users.