例句與造句

1. To array ccd , computing the interference pattern excursion based on image processing , fourier transform and interference pattern intensity distribution are discussed
   對于面陣ccd ，提出了基于圖像處理、傅里葉變換以及條紋亮度分布計算條紋漂移量三種方法。
2. The binarization , dilation and thinning of interference pattern are stressed . computing the excursion of interference pattern based on fourier transform is based on the fact that interference pattern has different phase at different position , the signal extraction of interference pattern and phase unwrapping algorithm are mainly discussed . computing the excursion of the interference pattern based on the interference pattern intensity distribution is to position the fringe according to the intensity distribution characteristic
   基于圖像處理計算干涉條紋漂移量，目的是抽取干涉條紋的骨架，通過條紋骨架的定位實現(xiàn)對條紋的定位，重點討論了條紋圖像的二值化、膨脹和細(xì)化；基于傅里葉變換計算干涉條紋的漂移量，是基于條紋不同位置處的相位不同這一事實，重點討論了干涉條紋信號的提取和干涉條紋相位去包裹算法；基于條紋亮度分布計算條紋漂移量，是根據(jù)條紋自身亮度分布的特點對條紋進(jìn)行定位。
3. Previous researchers have always determined the sp atial distribution patterns ( sdp ) of castanopsis kawakamii with a sample - dis tance method . however , the distribution patterns may be affected by the quadrat si ze and , in the course of analysis , the density differences among the cluster plots are not considered ; therefore , differences of cluster plot size and the dispersi on degree among individuals of cluster plots can not be known . authers of this pa per have determined the spatial distribution patterns of castanopsis kawakamii population in different habitats by means of non - quadrat distance method and a nalysed the pattern intensity and grain of the sdp . the pattern intensity is defi ned with the relative density differences and the pattern grain can embody the d ispersion degree of the individuals in the plots , and the dispersion degree among the plots . the determined results are as follows . the intensities of the species range in order from strong to week : litsea mollifolia p . kawakamii i . purpure a r . cochinchinensis c . kawakamii c . carlessii d . oldphamii s . superba . the gra ins of the species queue in order from coarse to close : s . superba = litsea mollif olia r . cohinchinensis c . kawakamii = i . purpurea c . carlessii p . racemosam d . oldp hamii . these determined results tally basiclly with the results authers of this paper have got in determining the same plots by means of aggregate index access ing method . in view of this , it is held that the sdp of c . kawakamii is closely related to the habitats and biological features
   前人都是采用樣方方法對格氏栲種群數(shù)量的空間格局進(jìn)行測定，而格局分布有可能受樣方大小的影響，且分析過程中沒有涉及聚塊間密度差的問題，因而無法掌握種群的聚塊大小差別及聚塊內(nèi)個體間的離散程度.本研究采用無樣方距離法，測定不同生境的格氏栲種群空間格局，分析格氏栲種群格局的強(qiáng)度和紋理.強(qiáng)度以聚塊和間隙的密度差來定義，紋理則是體現(xiàn)聚塊內(nèi)個體間的離散程度與諸聚塊間的分離程度.測定結(jié)果表明，格氏栲種群格局強(qiáng)度從高到低排列次序為：木姜子蚊母樹冬青茜草樹格氏栲米櫧虎皮楠木荷；格局紋理從粗到細(xì)的順序是：木荷=木姜子茜草樹格氏栲=冬青米櫧蚊母樹虎皮楠.這一測定結(jié)果與作者采用聚集度指標(biāo)測定相同樣地格氏栲種群空間格局的結(jié)果基本相符.因此，格氏栲空間格局類型及分布與格氏栲生物學(xué)特性及生境的關(guān)系密切
4. It's difficult to find pattern intensity in a sentence. 用pattern intensity造句挺難的