一種散斑模式的噪聲統(tǒng)計(jì)模型與自適應(yīng)濾波方法
A STATISTICAL NOISE MODEL OF SPECKLE PATTERN AND AN ADAPTIVE FILTERING APPROACH
-
摘要: 本文介紹了一種實(shí)際散斑模式的數(shù)學(xué)模型和噪聲統(tǒng)計(jì)模型,并提出了一種針對這種模型的自適應(yīng)次優(yōu)濾波方法。文中在分析了散斑模式及其噪聲性質(zhì)的基礎(chǔ)上,利用其局部方向性特征,結(jié)合最優(yōu)線性濾波器和非線性濾波器的特點(diǎn),對線性最小均方誤差濾波器進(jìn)行了自適應(yīng)逼近。實(shí)驗(yàn)結(jié)果表明,對散斑模式而言,本文的濾波方法與其它常用的圖象濾波方法相比,具有更好的去噪和邊緣保護(hù)性能,并且具有較好的濾波韌性。
-
關(guān)鍵詞:
- 散斑模式; 噪聲; 自適應(yīng)濾波
Abstract: A statistical noise model and a mathematical model for real speckle pattern are presented, and then, in view of the models, a new adaptive suboptimal image filtering approach is proposed. The proposed approach, with the local direction features of speckle pattern, combines the characteristcs of optimal linear filter with non-linear filter and is an adaptive approximation to linear minimum mean square error filter. Experimental results show that the proposed approach has fairly good edge-preserved performance, compared with other present image filters, as well as much better filtering performance and robustness for speckle pattern. -
Pratt W K. Dighal Image Processing.[J].New York: John Wiley Sons Inc.1978,:-[2]Kuan D T, Sawchuk A A, et al. IEEE Trans. on ASSP, 1987, ASSP-35(3): 373-382.[3]Kuan D T, Sawchuk A A, et al. IEEE Trans. on PAMI, 1985, PAM1-7(3): 165-177.[4]Erf. R K. Speckle Metrology, Academic Press. Inc., 1979.[5]于曉晗,袁保宗.自動化學(xué)報,1990,16(4): 347-351.[6]周新倫.通信學(xué)報,1983,4(2): 51-58.[7]Mastion G A. Compu[J].Vis. Graph. image Processing.1985, 31(1):103-121[8]Crimmins T R. Applied Optics, 1985, 24(10): 1438-1443.[9]丁潤濤.電子學(xué)報,1989,17(5):40-46. -
計(jì)量
- 文章訪問數(shù): 2004
- HTML全文瀏覽量: 105
- PDF下載量: 608
- 被引次數(shù): 0
下載:
