spectral classification 中文意思是什麼

spectral classification 解釋
光譜分類
  • spectral : adj. 1. 鬼的；鬼怪（似）的。2. 【物理學】光譜的。
  • classification : n 1 選別；分等，分級；分選。2 【動、植】分類（法）。 〈分類級別為： phylum 【動物；動物學】及 div...
  1. And understanding and studying the spectral features and variation rules of geo - targets in the experimental area, raising that it is the basis of geo - targets information collection with imaging spectrometer data to understand spectral features and variation rules of geo - targets, realizing that in a great extent spectral - integrated - form - based classification method can remove the phenomenon of " different spectrum with same objects " resulted from reflection ratio curve translation because of the angle change among sensor, targets and observation direction, and the average and variance images can be introduced to solve the problem of two kinds of geo - target with similar spectral forms and much different values of whole reflection ratio. it is suggested that " red edge " range bands of vegetation, which has close relationship with vegetation cover and biomass, is the main characteristic bands and important basis for careful vegetation classification and quantitative retrieval, and pixel - based derivative spectral analysis is very useful for removing the effects of soil background values and quantitatively retrieving vegetation biomass and cover. the remote sense quantitative retrieval model is developed for main appraisable factors of desertification monitoring assessment with imaging spectrometer data and then the applicability of model is analyzed

    研究結果如下：首先針對荒漠化地區的地物特徵，對高光譜數據不同波段的數據質量、波段組合進行了評價，提出了適用於荒漠化監測的基本波段選擇集；初步了解和掌握了研究地區的地物光譜特性及變異規律，進一步明確了掌握地物光譜特徵和變異規律是用成像光譜儀數據提取地物信息的基礎；發現了基於光譜整體形狀的分類方法在很大程度上能夠消除由於傳感器、地物目標觀測方向之間的角度變化引起的反射率曲線整體平移的「同物異譜」現象，對于譜形相似而整體反射率的值相差較大的兩類地物，通過引入均值和方差圖像參與分類得到解決；研究還表明在植被「紅邊」范圍內的波段是進行荒漠化監測的主要特徵波段，這些波段與植被生物量和蓋度都有密切的關系，是開展精細植被分類研究和植被定量反演的重要基礎；像元的導數光譜分析可以消除土壤背景的影響，是進行植被生物量和蓋度定量反演的有力工具；建立了荒漠化監測主要評價因子的定量反演模型，並分析了模型的適用性。
  2. In this paper, we made an investigation into texture feature extraction and classification based on statistic method and its application in multi - spectral image classification. the research works of this paper have been done as follows : firstly, in order to overcome the weakness of gray level co - occurrence matrix ( glcm ), a new unsupervised texture segment algorithm, based on multi - resolution model, is presented in this thesis

    本文主要研究了基於紋理統計特性的特徵提取與分割方法，並將其用於實際的多光譜圖像分類，具體工作如下:第一，針對傳統灰度共現陣方法中特徵提取的尺度單一問題，本文提出了一種多分辨無監督紋理分割演算法。
  3. This paper presents the principle and the maximum resolution of the spectral imaging followed by taking a case study as an example to discuss the application of this technique to sedimentary facies classification and the practical significance of it in progradation and retrogradation identification of sedimentary environment

    從理論基礎分析出發，首先介紹了頻譜成像的原理、最大解析度，然後結合國內某油田的實際情況，闡述用頻譜成像技術進行沉積相劃分以及判斷沉積環境水進水退的方法及實際效果。
  4. Automated spectral classification of broad - line and narrow - line active galactic nuclei based on k - nearest neighbour

    近鄰方法的窄線與寬線活動星系核的自動光譜分類
  5. After analysis of tm / etm + data ' s advantage over the forest change detection, tasseled cap transformation, principal component analysis and normalized difference vegetation index were chosen to enhance the vegetation spectral information. expert classification system was adopted to extract the main tree species in the littoral shelter forest

    在分析etm +數據在森林資源監測中的優勢的基礎上，通過纓帽變換、主成分分析和植被指數法增強植被光譜信息，結合專家分類系統對沿海防護林主要樹種進行提取。
  6. The result of the estimation demonstrated that the fused images had higher spatial resolution while maintaining the basic spectral contents of the original tm images, and the visual effect and the accuracy of the classification bad been greatly enhanced

    評價結果顯示，融合后的圖像既保留了多光譜圖像的豐富光譜信息，又不同程度提高了空間分辨能力，很大程度上改善了目視解譯效果和自動分類效果。
  7. At last, according to the significant spectral correlation of structure within the hyperspectral images, we propose a hyperspectral image lossless compression algorithm based on classification and prediction

    最後根據高光譜圖像譜間的結構相關性，提出一種基於分類預測的高光譜圖像無損壓縮演算法。
  8. A convenient classification of stars is based upon the observed sequence of spectral types.

    一種實用的恆星分類法是基於測得的光譜類型序列。
  9. In this paper we studied the textural features extraction, remote sensing images classification and bp neural network techniques and their applications in the meteorological problems such as recognition of the cloud cluster feature, cloud - drift wind retrieval and heavy rain process analysis etc. to the question of the low precise recognition of satellite images by using spectral features, the proposed approach assumes to perform a multiple analysis based on an advisable decision - making model by first developing a mixed pixel model which was based on the textural features of images, and then improving the recognition intelligence

    本文對模式識別領域中的圖像紋理特徵提取、遙感圖像分類、 bp神經網路與紋理特徵組合分類等方法，以及它們在雲團屬性識別、雲跡風反演和暴雨過程分析等氣象問題中的應用作了研究。針對過去利用圖像光譜亮度特徵進行識別分析氣象衛星圖像準確度不高的問題，本文提出了發展混合像元的分解模型，以圖像的紋理特徵為基礎，提高圖像識別的智能水平，以實現在分析決策模型的支持下，快速準確的復合分析的解決方案。
  10. In section three, the classification of bicyclic graphs is firstly presented according to the different positons of its two bicycles, and then the general regularity of calculation to spectral moments of bicyclic graph is discussed. the final part comes to some regular conclusions of spectral moment order which based on the parameter change of bicyclic graphs

    在第三部分中，我們首先按照雙圈圖中雙圈的相對位置的不同給出了雙圈圖的一個分類，其次研究了任意雙圈圖的譜矩計算的一般規律，最後針對三類圖的參數的變化給出了譜矩排列的規律性結論。
  11. It is a new approach to improve the accuracy of image classification in combining spectral feature with texture and structural features of ground objective on satellite image. based on the recognizable characteristics of satellite image, it is introduced how to describe and capture texture and structural features of ground objective by the discrete fractional brownian motion model. furthermore, neural networks are used for classification tool of satellite image. in classification spectral feature, texture and structural features of ground objective are used for the category of an irs - 1c satellite image. the category result shows this approach is better than the maximum likelihood classifier

    根據衛星數字圖像特點，引入了分形方法來描述紋理結構特徵，利用離散分形布朗運動dfbm統計模型來抽取衛星圖像紋理結構特徵。在此基礎上，採用神經網路方法將紋理結構特徵與地物光譜特徵相結合，進行衛星圖像分類。試驗結果表明，該分法分類效果優于單純採用光譜特徵分類的最大似然法。
  12. Absorption - band parameters such as the position, depth, width, and asymmetry of the feature have been used to quantitatively estimate composition of samples from hyperspectral data. so spectral absorptions are very important feature bands in use of hyperspectral classification and targets identify, this paper extracts absorption features of actual hyperspectral image by continuum removed method which is very useful. then tested both of them by

    吸收峰波段參數例如波長位置、深度、寬度、斜率、對稱度、面積等常常被用來定量的估計高光譜樣本的組成，因此光譜的吸收峰是高光譜識別分類應用中很重要的特徵波段，論文通過包絡線去除這種很有效的光譜分析工具提取出了實際的高光譜圖像的地物光譜的吸收峰參數。
  13. We estimated the fusion images in both subjective factors and objective factors. the objective parameters involved entropy, average gradient, spectral divergence, correlation coefficient and the accuracy of the classification

    對融合后的圖像分別從主觀和客觀兩個方面進行了定性和定量的評價，其中客觀評價分別採用了熵、平均梯度、光譜差異、相關系數以及分類精度作為評價標準。
  14. The distribution of line - spectrum and its harmonics extracted from the spectral envelope of different target ' s radiated noise exhibits strong differences, which may provide important clue for the detection and classification of targets

    摘要不同類型目標輻射噪聲包絡譜中的線譜及其諧波分佈存在較大差異，是進行目標檢測和分類識別的重要線索。
  15. Improvement of technique for hyper - spectral images classification

    高光譜影像處理方法的改進
  16. The results show that the maximum likelihood classification based on variogram texture and spectral bands can perfectly define the grades of beach sandy land and inner desertification, and the maximal classification precision comes up to 92. 4 %, which proves that geostatistical texture is effective in the application of desertification monitoring

    結果表明，運用變異函數紋理結合光譜波段的最大似然分類方法能夠很好地界定海灘沙地和內陸荒漠地的等級，最高分類精度達到92 . 4 % ，證明了基於地質統計學的影像紋理在實現該地區遙感荒漠化監測方面的有效性。
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