基于方向小波變換的高斯噪聲圖像恢復(fù)方法

1、 992 吉 林 大 學(xué) 學(xué) 報(bào) (理 學(xué) 版 第 48卷 圖 5 3 幅測試原圖像 ( A ( C及加噪 圖像 ( D ( F F ig . 5 T hree or iginal i m age s ( A ( C and corrup ted i m ages ( D ( F 圖 6 標(biāo) 準(zhǔn)小波閾值去噪結(jié)果 ( A ( C和方向小波閾值去噪結(jié)果 ( D ( F F ig. 6 Resu lts of th reshold denoising m e thod based on the standard wavelet transfor m ( A ( C and results of th

2、reshold denoising m ethod based on th e d irectional wave let tran sfor m ( D ( F 圖 7 標(biāo) 準(zhǔn)小波相關(guān)去噪結(jié)果 ( A ( C和方向小波相關(guān)去噪結(jié)果 ( D ( F F ig . 7 Re su lts of correlation denoising m e thod based on the standard wavele t transfor m ( A ( C and resu lts of correlation deno ising m ethod based on th e d irectiona

3、l wave let tran sform ( D ( F 第 6期 張 震 , 等 : 基于方向小波變換的高斯噪聲圖像 恢復(fù)方法 993 綜上, 本文提出了一種基于方向小波變換的圖像去噪方法 , 通過引入基于柵格理論的取樣方法, 解決了離散域中沿任意給定方向進(jìn)行變換的問題, 保留了標(biāo)準(zhǔn)小波變換可分離性和低計(jì)算復(fù)雜度的特 點(diǎn) , 捕捉方向信息的能力更強(qiáng) ; 去噪過程將基于標(biāo)準(zhǔn)小波變換的閾值及相關(guān)去噪方法運(yùn)用于方向小波 變換中 , 突破了標(biāo)準(zhǔn)小波變換僅沿固定方向變換去噪的限制, 有利于削弱 G ibbs效應(yīng) , 對去噪后圖像 的邊界保護(hù)具有積極作用 . 實(shí)驗(yàn)結(jié)果表明, 本文方法去噪效果明顯優(yōu)于對

4、應(yīng)的標(biāo)準(zhǔn)小波變換方法 . 但 本文方法計(jì)算復(fù)雜度較高 , 是對應(yīng)標(biāo)準(zhǔn)小波變換方法的 5倍 . 參 1 2 3 4 5 6 7 8 9 10 11 12 考 文 獻(xiàn) P itas I , V enetsanopoulos A N. N on linear D ig ita l F ilters: P rinc iples and A pp lications M . Boston: K luwe r A cadem ic , 1990 . Coy le E J , L in JH, G abbou jM. O pti m al Stack F ilte ring and the E sti m

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