點噪聲 的英文怎麼說

中文拼音 [diǎnzàoshēng]
點噪聲 英文
spot noise
  • 點 : Ⅰ名詞1 （液體的小滴） drop （of liquid） 2 （細小的痕跡） spot; dot; speck 3 （漢字的筆畫「、」）...
  • 噪 : 動詞1. （蟲或鳥叫） chirp 2. （大聲叫嚷） make noise; make an uproar; clamour
  1. To corner feature, both gradient magnitude change and direction change of gradient vector are discontinuity in a local image neighborhood, hence gradient - direction variation and gradient magnitude are used as another decision rule of the corner detection to improve antinoise

    為了提高抗噪聲，根據角特徵不僅灰度變化是不連續的，且相對周圍其他點的梯度方向也是不連續的，提出利用梯度角變化和梯度幅值作為角特徵檢測的另一個準則。
  2. Speckle noise suppression and filtering methods for spaceborne sar images

    圖像的斑點噪聲抑制與濾波研究
  3. Experimental result shows the algorithm has nearly the same edge preserving performance as nonlinear multiwavelet transform, and nearly the same speckle noise suppression performance as filtering

    此演算法對原圖像進行多小波變換，然後在不同尺度，不同方向進行自適應閾值處理，模擬結果表明：本演算法能夠有效地抑制了斑點噪聲，又保留有用信號及邊緣信息。
  4. Their advantages are : can cut down the " mosaic effect " distinctly, and at the same time, let the image deblur, omit the gray skip which is similar with the spot noise too

    其優點是：可同時顯著地減少放大馬賽克效應、圖像模糊和類點噪聲的灰度躍變等問題，顯著提高了電視墻放大圖像質量。
  5. First, we must filter the image to reduce noises, this process includes two phase : one is using the nearest neighbor middle filter ( knnmf ) to reduce the isolated noises, the other is using gauss filter to remove white noises

    首先對圖像進行濾波去除噪聲。濾波包括兩個階段：一是進行最近鄰中值濾波（ knnmf ） ，以去除孤立點噪聲，再進行高斯平滑，去除白噪聲。
  6. The noise in chu tiantai was highest, while plum garden was lowest

    景點噪聲以楚天臺為最高，梅園最低。
  7. The filtered results to a real interferogram showed the proposed method is powerful to interferogram speckle noise reduction, as well as it can preserve fine details in the interferogram that are directly related to the ground topography and maintain phase values distribution

    對一幅干涉相位圖的濾波結果表明，該演算法很好的抑制了斑點噪聲，極大的降低了殘余點的數量，保持了條紋邊緣和相位細節信息，並使絕對相位保持在一定的動態范圍。
  8. In chapter 3 traditional algorithms of suppressing speckle are discussed. the main parameters for evaluating the quality of image are introduced

    第三章分析了常見的斑點噪聲抑制演算法，介紹了主要的圖像質量評估指標。
  9. In chapter 6 we research on a denoising technique through shrinking the wavelet coefficients adaptively, then fuzzy membership in fuzzy mathematics is introduced to put forward wavelet fuzzy snr to evaluate quality of sar images based on it. experiment results and academic analyses show its efficiency

    第六章研究了小波系數自適應收縮演算法抑制斑點噪聲，在此基礎上引入模糊數學中隸屬度的概念，提出了一種新的評估sar圖像質量的指標一小波模糊信噪比。
  10. Both filtering methods can significantly reduce speckle noise, and at the same time preserve the image notable details

    兩種演算法都可以在濾除斑點噪聲的同時較好地保留圖像的突出細節特徵。
  11. In this paper, a nonlinear multiwavelet transform adaptive threshold value method is proposed to suppress speckle noise

    摘要文章提出了一種新的用於斑點噪聲抑制的非線性多小波變換自適應閾值演算法。
  12. The arising mechanism, model and statistical characteristics of speckle noise are described and the popular filters are analyzed

    首先介紹了斑點噪聲產生機理、模型和統計特徵，對常用的圖像濾波器進行了分析。
  13. Wavelet transform also has time - frequency orienting ability and realize the abruption of the balanced and unbalanced component in images. this paper, based on particularly expatiating information characters in sar image data, will investigate compression algorithm applying for sar images by analyzing embedded encoding algorithms using wavelet theory. using several standards to evaluate our method and spiht algorithm, it is clear that our method outgoes spiht algorithm

    本文在對sar圖像數據的信息特徵進行了詳細闡述的基礎上，利用小波理論分析近年來比較流行嵌入式壓縮編碼方法，來研究適用於sar圖像的壓縮方法，取得以下研究成果： （ 1 ）考慮到sar圖像的動態范圍比較大，而且sar圖像斑點噪聲模型大部分是乘性噪聲，先對其進行對數變換，既可以縮小數據的動態范圍，也可以把乘性噪聲轉變成加性噪聲模型。
  14. Speckle in sar images will affect the precision of recognition, should be removed before classing

    Sar圖像的斑點噪聲對識別率影響較大，在目標識別前需把斑點從圖像中去除掉。
  15. In chapter 1 we particularly research the mechanism of speckle coming into being and the statistical characteristic of sar image

    第一章著重研究了斑點噪聲的形成機理及sar圖像的統計特性。
  16. Based on the above two points, algorithms research in speckle suppression and multi - source image fusion were chosen as the main topic in this paper

    本文針對以上兩個方面，對sar圖像斑點噪聲去除和多源遙感數據融合演算法進行了研究。
  17. In chapter 2 we particularly describe the mechanism of speckle forming, discuss the noise model and the statistical characteristic of sar image

    第二章首先討論了斑點噪聲的形成機理，研究了斑點噪聲模型，然後分析了sar圖像的統計特性。
  18. The result of the method is better than the traditional one. the segment filter method has been proposed also, whose result is better than filters directly

    本文還提出了先進行圖像分割再濾波的方法，它的濾波效果比直接進行斑點噪聲濾波的效果要好。
  19. Based on the multiplicative speckle model, a new filtering algorithm based on wavelet transform was developed. first, the multiplicative speckle noise was changed by logarithmic transform into additive noise, which simplified the subsequent speckle suppression. the speckle suppression was carried out in the process of wavelet transform of the logarithmic transformed image

    針對斑點噪聲的乘性模型特點，構造了一種基於小波分析的濾波器：對sar圖像進行對數變換，利用小波變換對對數圖像進行濾波處理，再通過指數變換得到去噪圖像。
  20. Supported by the foundation research project of jiangsu province ( the natural science fund no. bk2001047 ) " research on image quantitative evaluation of sar ", we discuss the statistical characters of sar image, speckle suppression and sar image evaluation etc. in the preface to this article, first, the basic purpose and significance of speckle smoothing and quantitative evaluation for sar images are introduced briefly

    本文結合江蘇省基礎研究計劃（自然科學基金no . bk2001047 ） 「合成孔徑雷達（ sar ）圖像定量評估研究」 ，分析研究了sar圖像的統計特性，對sar圖像的斑點噪聲抑制及質量評估等相關問題進行了研究。本文的第一章為緒論，簡要介紹了本文的研究目的及意義，國內外研究進展情況，以及本文主要的工作。
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