低信噪比圖象邊緣提取的非線性方法
A NONLINEAR METHOD FOR EDGE DETECTION OF LOW SNR IMAGE
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摘要: 針對(duì)低信噪比圖象的邊緣提取問題,本文提出了一種非線性方法,即利用大窗口平滑去噪性能強(qiáng)與小窗口提取邊緣性能好相結(jié)合的方法,此時(shí)采取大窗口濾波,小窗口中作非線性的微分算子求導(dǎo)。為了避免求導(dǎo)后閾值選取的盲目性,文中提出了一種噪聲引導(dǎo)的閾值確定準(zhǔn)則,并根據(jù)這個(gè)閾值分割圖象。在大窗口濾波中,采用了二維卷積等于兩個(gè)一維卷積級(jí)聯(lián)的技術(shù)壓縮濾波器的存儲(chǔ)空間。最后對(duì)這種方法進(jìn)行了性能評(píng)價(jià),并且給出了實(shí)驗(yàn)結(jié)果。
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關(guān)鍵詞:
- 圖象處理; 邊緣提取; 非線性微分算子; 指數(shù)濾波器
Abstract: A nonlinear method for detecting the edge of low-SNR image is developed. This method adopts the filtering in large window to smooth the noise and the nonlinear differential operator in small window to detect the edges. A criterion of noise-guided threshold selection is introduced to segment the derivative image so that the threshold can be determined automatically. In large window s filtering, the technique of 2-D convolution implementation by two 1-D convolutions in series is taken to reduce the storage space of the filter. Finally, the performance of this method is evaluated, and experimental results are given. -
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