Description: 图像分割源程序
通过融合处理，％ image segmentation based on multispectral image fusion
％ and morphology reconstruction watershed
％ main program
-image segmentation source through fusion, % image segmentation based on multispectral im age fusion% and morphology reconstruction wat ershed% main program Platform: |
Size: 1255 |
Author:li mingxi |
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Description: 图像分割源程序
通过融合处理，％ image segmentation based on multispectral image fusion
％ and morphology reconstruction watershed
％ main program
-image segmentation source through fusion, % image segmentation based on multispectral im age fusion% and morphology reconstruction wat ershed% main program Platform: |
Size: 1024 |
Author:li mingxi |
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Description: 些成熟的瓜果果实在单一的光谱图像中，果与叶的灰度值只存在微小差异，常用的图像分割方法不足以把果与叶区分开，为此，提出一种基于多光谱图像融合的形态学重构分割方法。-More mature fruits and fruit in a single spectral image, the fruit and leaves only a minor difference in gray scale, commonly used image segmentation approach is not sufficient to separate the fruit and leaf area, this paper, a multispectral image fusion morphological reconstruction segmentation. Platform: |
Size: 495616 |
Author:xiliao |
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Description: Building Extraction from Very High Resolution
Multispectral Images using NDVI based
Segmentation and Morphological Operators by Durgesh Singh Platform: |
Size: 930816 |
Author:durgesh singh |
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Description: 图像分割是一种重要的图像分析技术，对图像分割的研究一直是图像技术研究中的热点和焦点。分水岭算法是基于数学形态学理论的图像分割算法，但是对噪声敏感且存在过分割的现象。为提高图像分割效果，本文通过对影像进行滤波处理，用改进的快速区域合并算法优化分水岭算法进行影像分割。-In this work a technique for cloud detection and classification from MSG–SEVIRI (Meteosat Second Generation–Spinning Enhanced
Visible and Infra-red Imager) imagery is presented. It is based on the segmentation of the multispectral images using order-invariant
watershed algorithms, which are applied to the corresponding gradient images, computed by a multi-dimensional morphological operator.
To reduce the over-segmentation produced by the watershed method, a RAG (Region Adjacency Graph) based region merging
technique is applied, using region dissimilarity functions. Platform: |
Size: 2011136 |
Author:comewanlei |
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Description: Magnetic resonance (MR) images can be used to detect lesions in the brains of multiple sclerosis (MS)
patients and is essential for diagnosing the disease and monitoring its progression. An automatic method is
presented for segmentation of MS lesions in multispectral MR images. Firstly a PD-w image is subtracted its
corresponding T1-w image to get an image in which the cerebral spinal fluid (CSF) is enhanced. Then based on
kernel fuzzy c-means (KFCM) algorithm, the enhanced image and the corresponding T2-w image are segmented
respectively to extract the CSF region and the CSF combining MS lesions region. A raw MS lesions image is
obtained by subtracting the CSF region CSF combining MS region. By applying median filter and
thresholding to the raw image, the MS lesions are detected finally. Results are quantitatively uated on
BrainWeb images using Dice similarity coefficient (DSC). Finally, the potential of the method as well as its
limitations are discussed.-Magnetic resonance (MR) images can be used to detect lesions in the brains of multiple sclerosis (MS)
patients and is essential for diagnosing the disease and monitoring its progression. An automatic method is
presented for segmentation of MS lesions in multispectral MR images. Firstly a PD-w image is subtracted its
corresponding T1-w image to get an image in which the cerebral spinal fluid (CSF) is enhanced. Then based on
kernel fuzzy c-means (KFCM) algorithm, the enhanced image and the corresponding T2-w image are segmented
respectively to extract the CSF region and the CSF combining MS lesions region. A raw MS lesions image is
obtained by subtracting the CSF region CSF combining MS region. By applying median filter and
thresholding to the raw image, the MS lesions are detected finally. Results are quantitatively uated on
BrainWeb images using Dice similarity coefficient (DSC). Finally, the potential of the method as well as its
limitations are discussed. Platform: |
Size: 2048 |
Author:mahsy |
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Search - multispectral segmentation