entropy gradient 中文意思是什麼

entropy gradient 解釋
熵梯度
  • entropy : n. 1. 【物理學】熵。2. 【無線電】平均信息量。
  • gradient : adj. 1. 傾斜的。2. 【動物；動物學】步行的，能步行的。n. 1. 〈英國〉（道路的）傾斜度，坡度，坡路。2. 【物理學】梯度，陡度，（溫度、氣壓等的）變化率，梯度變化曲線。
  1. By two ways, this paper debates the theory of fracture detection : on one hand by the way of edge detection in image processing ; on the other hand by time series analysis. the detection by time series analysis is more antinoise than edge detection in image processing. edge detection theory in image processing mainly includes correlation data, fuzzy edge detection, entropy operator edge detection and gradient edge detection

    圖像處理中的邊緣檢測的方法主要包括相干數據體法、模糊邊緣檢測法、基於熵運算元的邊緣檢測法、梯度邊緣檢測法；其中模糊邊緣檢測法比較依賴于參數的選擇，其渡越點兩邊的像素區別明顯；熵運算元的檢測方法則是檢測的圖像邊緣比較光滑，連通性好；梯度檢測法可以使用不同的運算元核，演算法比較簡單；相干數據體對于總體的大的裂縫的分佈具有比較奸的反應。
  2. Then, a new regularized conjugate - gradient reconstruction algorithm was proposed for optical tomograpy, in which the ill - posedness of the reconstruction problem and as a result the quality of the reconstructed image are improved by introducing two regularization terms of image entropy and the local smoothing function

    其次，提出了一種正則化共軛梯度ot圖像重建演算法，通過引入圖像熵和局部平滑函數作為正則化項有效改善了重建問題中的病態特性，提高重建圖像的質量。最後，提出一種多解析度的ot圖像重建演算法。
  3. For focus measures, frequency spectrum functions, gradient functions and entropy function are analyzed in detail

    其次，本文從頻譜函數、梯度函數、熵函數等方面詳細分析了對焦深度法中常用的對焦評價函數。
  4. Firstly, the principle of phase gradient autofocus and rank one phase estimate and its advanced are detailed. secondly, it proposes an algorithm of fast maximum contrast phase compensation after discussing its similar algorithm fast minimum entropy phase compensation

    討論了經典的相位梯度自聚焦演算法、秩一相位誤差演算法及其改進形式;在討論快速最小熵相位補償演算法的基礎上，提出了對比度最優相位調整演算法，實測數據處理表明了該演算法的有效性。
  5. In this paper, two kind of wavelet based fusion algorithm of remote sensing images are improved. by experiments on tm images, the improved algorithms are both better than original ones according to the shanon entropy and mean gradient

    本文對傳統的基於小波的遙感圖像像素級融合演算法進行改進，並用tm圖像進行實驗，結果表明在信息熵和平均梯度等指標方面，改進后的演算法好於原演算法，起到了優化的作用。
  6. 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。
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