gaussian image 中文意思是什麼
gaussian image
解釋
高斯像-
Summarize the common image pre - processing methods and point out their merits and faults. discuss the boundary effect of gaussian low - pass filtering ( glpf ). to improve it, the zero - order gaussian filtering for an open profile ( gfo ) is used
討論了高斯低通濾波的邊界效應，利用零階開環高斯濾波演算法，對高斯低通濾波進行了改進，使濾波圖像在圖像大小不改變的情況下，邊緣處的濾波效果得到明顯的改善。 -
Texture image segmentation based on gaussian mixture models
基於高斯混合模型的紋理圖像分割 -
2. based on studying canny operator and log operator, we take wavelet edge detection in allusion to smoothing image extremely and losing weak edge existed in gaussian filter
（ 2 ）在分析canny邊緣檢測演算法和log邊緣檢測演算法的基礎上，針對高斯濾波器存在過度光滑圖像和丟失緩變邊緣的問題，採用基於小波變換的邊緣檢測演算法。 -
Based on unsupervised learning, sparse coding is suitable to describe images with non - gaussian distribution and can get rid of the high order redundancy among the image pixels. since the basis function of sparse coding has build - in clustering property, it increases the inter - class variations of the features
稀疏編碼是一種基於非監督學習的演算法，它適合描述具有非高斯分佈的數據對象，能夠有效地消除圖像象素點之間的冗餘，並具有內在的聚類特性。 -
Image segmentation ; textured image ; gaussian mixture models ; multiresolution wavelet ; em algorithms
圖像分割紋理圖像高斯混合模型多解析度小波em演算法 -
A systematic summary of previous work has been given first. then this paper presents a novel multi - stage face detection algorithm, which makes a good use of human face pattern ' s valuable information in colour image sequences. the difficult detection task has been divided into four steps : the preprocessing, which is to gain skin colored regions with human skin color model ; the roughly detection and face region refining by elliptic curve fitting ; the fine detection with facial features " detection and location ; the face / non - face classification step based on pca and gaussian density estimation technique
本文對彩色序列圖像中的人臉檢測和跟蹤技術進行了深入的研究，其具體內容為：對近年來的研究工作進行了系統的介紹；提出了一個由粗到細的多階段的人臉檢測演算法，該演算法充分利用了序列圖像中人臉模式的各種有用信息，將復雜的檢測工作分為了四個部分：膚色區域分割預處理，人臉粗檢及利用橢圓擬和的人臉區域提煉，應用人臉基本特徵檢測和定位的人臉細檢， pca結合高斯概率密度估計的人臉驗證。 -
The vq - based approach assumes a gaussian mixture distribution, which fits real - world image data reasonably well. after estimating this distribution through em method, this approach trains optimized vector quantizers to partition data space
該方法使用更適合真實圖像庫的高斯混合模型描述數據分佈，並訓練優化的矢量量化器劃分數據空間。 -
There are three steps of the concrete process of the algorithm : initial localization, separating image and confirmation. firstly, single gaussian model is used to imitate skin - color distribution, meanwhile, skin probability images which is smoothly disposed using middle wave is calculated to attain the initial localization. secondly, in order to separate the latent face region, it uses multimodal information that includes the region growing 、 the hue and brightness 、 skin probability images etc. at last, it adopts the criterion of morphology analysis and face characteristic draw to confirm the latent region
演算法的具體過程主要分為三個階段:人臉初定位、人臉分割和人臉確認，首先採用高斯模型來模擬膚色分佈並構造出膚色概率圖進行人臉的初定位，並對膚色概率圖採用中值濾波進行平滑處理，接著利用區域生長準則和融合色度、亮度以及膚色概率圖等多源信息相結合的方法對圖像進行分割，以達到分割出潛在臉區的目的，最後採用人臉整體形狀的確認準則和人臉特徵提取的確認準則相結合的方法對潛在臉區的最終確認。 -
On the basis of the authors ’ results published in this journal [ 67 ], this paper further proposed two strategies which improved both quality and speed of fractal encoding : one, a priori adding additive white gaussian noise into the image being encoded to reduce the domain blocks that are unlikely to meet the constraint on contrast scaling factors ; the other, range blocks with small standard deviations are directly approximated by the constant block ( i. e., all the
在筆者原有結果[計算機模擬， no . 8 ， 2004 ]的基礎上，本文提出進一步提高解碼圖像質量和編碼速度的方案:一是預先在待編碼圖像中添加高斯白噪聲以進一步減少不滿足對比度因子約束的domain塊的數目;二是對小方差range塊直接用其均值塊代替以進一步加快編碼速度。 -
In this paper, the main work includes : ( 1 ) through the detailed analysis of the mechanism of pcnn, we point out that the behaviors of pcnn actually means the reorganization of input information, and finally two methods ( including method for salt & pepper noise and method for gaussian noise ) for image noise removal based on pcnn are presented
本文的工作主要有： （ 1 ）通過對pcnn工作機理和運行行為的深入分析，揭示了pcnn的運行行為實際上是在對網路輸入信息進行重新組織，並在此基礎上給出了利用pcnn實現圖像濾波（包括圖像椒鹽噪聲和圖像高斯噪聲濾波）的演算法。 -
Finally, the design scheme of cellular automata image edge detect algorithm and gaussian random number generator algorithm applied in the system is presented, and an extended application scheme of data acquisition by the system is also provided
在此基礎上，提出了元胞自動機圖像邊緣檢測演算法和高斯隨機數產生演算法在系統中應用的設計方案，並給出了系統應用於數據採集的擴展方案。 -
The paper also analyzes synthetically the effects of some smooth filters prior to image segmentation and indicates that gaussian lowpass filter, a alterable scale filter, is a good choice to establish a balance between the reservation of image details and removal of noise. on the basis of current investigation of actuality and trend of image segmentation at home and abroad, the paper adopts marr operator, called by optimal edge detection to improve greatly efficiency of image segmentation and edge abstract. the sparse edge
論文在分析當前圖象分割的現狀和趨勢的基礎上，採用被稱為最佳邊緣檢測運算元的marr演算法，使圖象分割和邊緣提取的準確性得到了很大的提高；利用人機交互輔助的方法來搜索已經檢出的稀疏邊緣點，並用最小二乘法擬合這些邊緣點，使裝配間隙寬度的測量的精度和準確性得到了極大的保證。 -
Considering the payload when transmitted in gaussian channel according to information theory, the system builds up a mapping relationship between image space and watermarking space, and achieves the trade - off between theoretic capacity, robustness and perceptual distortion
考慮高斯通道傳輸時信息理論的容量，系統建立了圖像空間和水印空間的影射關系，實現了水印系統應用時的理論容載、魯棒性和人類感官之間的一種平衡關系。 -
The interpolation is applied widely in medical image processing. since the ideal interpolation function spatially is unlimited, several class of practical interpolation kernels have been introduced : piecewise local polynomials, windowed sinc, lagrange, gaussian et al. and their properties have been analyzed in spatial and frequency domain and from evaluation and result
插值在醫學圖像處理中應用非常廣泛，因為理想插值函數在空域無限擴展，論文引入了幾類實際插值核：分段局部多項式、加窗sinc 、 lagrange和gaussian等，並從空域、頻域、實現代價和實際效果上進行了分析和討論。 -
After converting multiple speckle noise to additional gaussian noise, we achieve the mmse estimate of sar image wavelet coefficient
將乘性噪聲轉化為近似加性高斯噪聲，可以獲得sar圖像小波系數的最小方差估計。 -
This method was divided into 4 steps : wiping out random noise by mean filter, reducing gaussian noise by gaussian filter, balancing brightness difference between stereo image pair through histogram equalization, and enhancing image edges and details by laplace sharpness
此方法分為4個階段：用均值濾波去除隨機噪聲；用高斯濾波去除高斯噪聲；用直方圖均衡化法平衡立體圖對間的亮度差異；用拉普拉斯銳化增強圖像的邊緣和細節。 -
Having precisely extracted feature points, we go into the image stabilization technique based on the gaussian pyramid
在對檢測特徵點充分研究的基礎上，深入探討了基於高斯金字塔的圖像穩定技術。 -
By applying generalized gaussian distribution to statistically model the alternating current coefficient of discrete cosine transform, the technology of the blind image watermark is studied and the performance of the new detector is analyzed
摘要根據數字圖像離散餘弦變換域交流系數的廣義高斯分佈模型，對盲圖像水印技術進行研究，並給出了水印檢測器檢測性能的理論分析結果。 -
Image stabilization based on adaptive gaussian mixture model
基於自適應高斯混合模型的圖像穩定方法 -
A range image segmentation algorithm based on gaussian mixture model
一種基於高斯混合模型的距離圖像分割演算法
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