Classification of Multispectral Image Data
A Comparative Analysis of Hyperspectral and Multispectral Image Classification Techniques
... The models with shallow and deep feature representations are used to determine the utility of self-taught training method [21]. Each model is trained on multiple unlabeled HSI datasets for adding spatiospectral variation ...
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New Fully Automatic Multispectral Image Classification based on Scatterplot Method
... It is remain to state that the shifting down and up constants beside the mean values of the VR(x) and NIR(x) axes, that have been suggested to represent the intersect point between the wet-dry and the soil lines, are ...
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SHIP CLASSIFICATION FROM MULTISPECTRAL VIDEOS
... the image processing stage is to detect moving objects on multispectral videos (Manolakis et ...background image for both visible and infrared videos is periodically refreshed while acquiring videos ...
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Wavelet Based Classification of Multispectral Satellite Image Using Fuzzy Incorporated Hierarchical Clustering With SVM Classifier
... suitable image is obtained for segmentation. The processed image consists of thousand of pixels and to classify the image based on of pixels is time ...input image is clustered based on the ...
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Land Cover Classification Using IRS-1D Data and a Decision Tree Classifier
... basic data layers in geographic information system for physical planning and environmental ...Digital image classification is generally performed to produce land cover maps from remote sensing ...
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Hyperspectral Image Segmentation and Classification using FODPSO
... acquire data mostly from the visible through the middle infrared wavelength ranges and can simultaneously capture hundreds of (narrow) spectral channels from the same area on the surface of the ...increased ...
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A novel unsupervised Levy flight particle swarm optimization (ULPSO) method for multispectral remote sensing image classification
... Unsupervised classification (i.e. clustering) of remote sensing image, an important means to acquire land use/cover information, has become increasingly in demand due to its simplicity and ease of ...hard) ...
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HYPERSPECTRAL CLASSIFICATION FOR IDENTIFYING DECAYED ORANGES INFECTED BY FUNGI
... hyperspectral image with full wavelengths because this implies a very high time-consuming for high-dimensional data ...a multispectral system for the needs of practical ...(PC) image was a ...
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Monitoring Cotton Root Rot Progression within a Growing Season Using Airborne Multispectral Imagery
... Image Classification. The rectified, four-band multispectral images were classified into two to twenty spectral classes using ISODATA (Iterative Self-Organizing Data Analysis) unsupervised ...
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A Comparative Analysis of Image Fusion Techniques for Remote Sensed Images
... complementary data to enhance the information apparent in the images as well as to increase the reliability of the ...accurate data and increased utility in application fields like segmentation and ...of ...
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Portable Multispectral Colorimeter for Metallic Ions Detection and Classification
... multispectral sensor as the detector and the white light emitting diode has been used as an excitation source. All components of the system such as excitation, detection and test calibration curves have been ...
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Annual and Seasonal Shoreline Evolution of Tainan Gold Coast Using Multiband Satellite Images
... Wave data were measured by the Institute of Harbor and Marine Technology (IHMT), as an affiliate to the department of transportation of the Taiwan provincial government, with the Nortek AWAC mounted at offshore ...
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Invariant representation for spectral reflectance images and its application
... and stability characteristics. Combining the photometric quasi-invariants with derivative-based feature detectors led to features which could identify shadow corners and object corners [5]. Stokman and Gevers [7] ...
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Image Enhancement Using Discrete Curvelet Transform
... the image using the concept of curve lets and multi structure decomposition and morphological ...input image into different sub ...contrast image analysis ...
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A Survey on Various Classification Techniques for Medical Image Data
... CART algorithm was developed by Brieman, Friedman, Olshen and Stone in 1984 [2]. CART creates trees that have binary split on nominal or interval inputs for a nominal, ordinal or interval target. The CART algorithm does ...
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Study on Computer Generated Electromagnetic Effects on Computer Users
... The extraction of spectral information related to this type of target the Linear Imaging Self Scanning (LISS-III) imagery has been accomplished through the use of image processing methods such as principal ...
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Classification of Cardiotocography Data with WEKA
... of data mining techniques had contributed in handling of new kinds of data types and ...of data mining and its application in medical domain is still young enough so that the possibilities of the ...
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Application of Image Processing for Classification and Quality Evaluation of Wheat
... Digitalized image analysis may be an advantageous method to distinguish varieties of different grain ...to classification and quality feature determination of wheat ...provide image process-based ...
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Diabetes data prediction using data classification algorithm
... the classification algorithms are compared by utilizing matrix and classification ...diabetes data for his effort and the decision tree using WEKA has been used to put up the prediction ...Diabetic ...
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Multispectral band image compression using wavelets
... Wavelet Transform coding provides many attractive advantages over other transform methods. One major advantage of wavelet analysis is its ability to perform local analysis-to analyze a localised area of a large signal. ...
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