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Image processing；Image restoration；Random channel；Total least square algorithm
|Issue Date: ||2013-05-02T03:47:14Z
|Abstract: ||摘要:由於影像在隨機通道下傳送時容易造成雜訊干擾和模糊效應,本計畫採用本人提出的限制性全體最小方差法(CTLS),做為影像復原的理論基礎。然而CTLS演算法在二維影像復原時所需的計算量頗大,為了降低計算複雜度,本計畫提出共軛梯度和離散傅立業轉換域兩種實現CTLS的方法。 此外,為了消除共軛梯度法於影像邊緣所產生的環狀假象,採用權重空間範數的觀念,使得演算法可依影像的相鄰像素變化的情形,來調整調制項的權重值,而達到消除環狀假象的目的。最後以電腦模擬的結果,來驗證所提演算法的效能。|
abstract:The method of Constrained Total Least Squares (CTLS) proposed by the author  is adopted in this project as a framework for restoring images degraded by noise and blur, when transmitted over a random channel. However, CTLS requires large computational complexity for the purpose of 2-D image restoration. In order to reduce computational complexity, the conjugate gradient method and the DFT frequency-domain method are proposed for the realization of CTLS in the project. In addition, the concept of matrix norm in the weighting space is adopted in the regularization term of the conjugate gradient method in order to eliminate ringing artifacts near the boundary (edge) regions. This mechanism provides the underlying algorithm with adaptation feature; the weights in the regularization term can be adjusted according to the local property of pixel value changes in the image of interest. Finally, computer simulation results are provided to show the effectiveness of the proposed algorithms.
|Appears in Collections:||[電機工程學系] 研究計畫|
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