本文在BayesShrink 閾值的基礎(chǔ)上，提出了一種計算更有效的自適應(yīng)的閾值估計，并
針對傳統(tǒng)的軟、硬閾值函數(shù)在去噪中的不足，提出一種新的去噪閾值函數(shù)，最后將所提出的圖象去噪方法與傳統(tǒng)方法進行了實驗比較，實驗結(jié)果表明該方法在圖象去噪中取得較好的效果，有效地提高了信號去噪所得信噪比增益。
關(guān)鍵詞：正交小波變換、圖象去噪、閾值
An Improved Algorithms of Image Denosing Based on Orthogonal Wavelet Transform LEI Hui ( School of Electrical and Infomational Engineering, Changsha University of Science & Technology,Changsha,410076) Abstract：This paper proposes an efficient threshold estimation method for image denoising based on BayesShrink. So the traditional methods for noise reduction using wavelet soft threshold function and hard threshold function have some defects, an improved threshold function is proposed, At the end, experiments have been done between this new method and the traditional methods. The experiment results indicate that this new method achieves better effect on reducing noise and gets higher SNR gain for the reconstructed signal.
Keywords: orthogonal wavelet transform, Image denoising, threshold