【摘要】：利用聲吶進(jìn)行水下目標(biāo)定位識(shí)別是當(dāng)前水下目標(biāo)識(shí)別與跟蹤的重要手段之一,由于聲吶圖像受噪聲影響嚴(yán)重、分辨率低,對(duì)聲吶圖像的背景建模有助于其目標(biāo)分割與識(shí)別。首先,分析聲吶圖像背景區(qū)域灰度的統(tǒng)計(jì)特性,結(jié)合其特點(diǎn)采用高斯分布、Gamma分布、威布爾分布、瑞利分布模型對(duì)6類(lèi)不同背景區(qū)域聲吶圖像統(tǒng)計(jì)特性進(jìn)行擬合,構(gòu)建聲吶圖像背景區(qū)域模型。最后,采用?2準(zhǔn)則和Kolmogorov距離誤差評(píng)價(jià)準(zhǔn)則評(píng)估擬合效果。擬合結(jié)果表明,高斯分布、Gamma分布和威布爾分布均能較好地逼近聲吶圖像背景區(qū)灰度統(tǒng)計(jì)特性。為滿(mǎn)足實(shí)時(shí)性的應(yīng)用需求,選用高斯分布構(gòu)建聲吶圖像背景灰度統(tǒng)計(jì)模型是可行、合理的方案,從而為聲吶圖像預(yù)處理和目標(biāo)分割提供了背景模型建模的理論依據(jù)。
[Abstract]:Underwater target location and recognition using sonar is one of the important methods of underwater target recognition and tracking. Because sonar image is seriously affected by noise and has low resolution, the background modeling of sonar image is helpful to its target segmentation and recognition. Firstly, the statistical characteristics of sonar background region are analyzed, and the statistical characteristics of sonar images are fitted by Gao Si distribution Gamma distribution, Weibull distribution and Rayleigh distribution model. The background region model of sonar image is constructed. Finally, adopt? The fitting effect is evaluated by 2 criteria and Kolmogorov distance error evaluation criterion. The fitting results show that both the Gamma distribution and Weibull distribution of Gao Si distribution can approach the statistical characteristics of the background region of sonar image. In order to meet the requirement of real-time application, it is feasible and reasonable to select Gao Si distribution to construct the background gray scale statistical model of sonar image, which provides the theoretical basis for the background model modeling for sonar image preprocessing and target segmentation.
【作者單位】： 三峽大學(xué)水電工程智能視覺(jué)監(jiān)測(cè)湖北省重點(diǎn)實(shí)驗(yàn)室;三峽大學(xué)計(jì)算機(jī)與信息學(xué)院;
【基金】：國(guó)家自然科學(xué)基金(聯(lián)合基金)重點(diǎn)項(xiàng)目(U1401252);國(guó)家自然科學(xué)基金資助項(xiàng)目(61272237) 湖北省重點(diǎn)實(shí)驗(yàn)室開(kāi)放基金項(xiàng)目(2015KLA05)
【分類(lèi)號(hào)】：TB56;TP391.41

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