imagery processing method 中文意思是什麼
imagery processing method
解釋
成象處理方法-
A processing method for remote sensing imagery data based on bayesian network model
基於貝葉斯網路模型的遙感圖像數據處理技術 -
Independent component analysis ( ica ) is a new multi - dimensional signal processing technology developed from blind source separation of late years. some scholars have brought forward a new polarimetric speckle reduction method by using independent component analysis which based on the multi - polarimetric trait of polarimetric sar and the independence between speckle and texture of sar imagery. while the algorithm thinks that there is only one real scene in polarimetric sar source images, so they get only one recovering image in the procedure of image separation and lose polarimetric property
獨立分量分析是近年來由盲源分離技術發展來的一種新的多維數字信號處理技術，通過計算數據的高階統計信息，可以僅從觀測信號中估計出互不相關且盡可能相互統計獨立的被未知因素混合的原始信號的估計信號，從而幫助實現信號的增強和分析。 -
The main work is as follow : the pater makes use of vanguard genetic algorithms in image segmentation, uses vanguard genetic algorithms to get the image threshold. using this method we may get different grey vehicles from the background exactly. used the support vector machine theory to conduct the vehicles automatic sorting simulation research, the simulation result had proven this method could quite be accurate carries on the vehicles type the recognition ; improved based on the background automatic renewal hypothesized examination region algorithm, enhanced timeliness and the accuracy which the vehicles examines ; and to has carried on the specify based on the hypothesized examination region imagery processing algorithm realization ; in the paper also introduced withdraws the algorithm based on the gradation continuous movement vehicles characteristic to carry on the vehicles the characteristic to withdraw as well as to use the localization method which colored filter same gradation chart processing unifies to carry on the realization method which the vehicles license plate locates
本文根據智能交通控制與模擬對于交通流量、車輛到達率、車輛速度等交通信息檢測的需求，基於視頻圖像進行了交通信息處理的演算法研究與實現，主要工作包括以下幾個方面:將先鋒遺傳演算法應用到圖像閾值分割中，利用先鋒遺傳演算法尋求全局最優閾值，可以比較準確的將圖像中不同灰度的車輛從背景中分離出來;採用支持向量機理論進行了車輛自動分類的模擬研究，模擬結果證明該方法能夠比較準確的將車輛的類型進行識別;改進了基於背景自動更新的虛擬檢測區域演算法，提高了車輛檢測的實時性和準確性;並對基於虛擬檢測區域的圖像處理演算法實現進行了詳細說明;論文中還介紹了基於灰度連續性的運動車輛特徵提取演算法進行車輛的特徵提取以及採用彩色過濾器同灰度圖處理相結合的定位方法進行車輛牌照定位的實現方法。
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