scholarly journals THE ROLE OF TEXTURE INFORMATION AND DATA FUSION IN TOPOGRAPHIC OBJECTS EXTRACTION FROM SATELLITE DATA

2014 ◽  
Vol 40 (3) ◽  
pp. 116-121 ◽  
Author(s):  
Kuldeep Chaurasia ◽  
Pradeep Kumar Garg
Keyword(s):  
Data Fusion ◽  
Information Extraction ◽  
Satellite Data ◽  
Satellite Images ◽  
City Planning ◽  
Window Size ◽  
Accurate Information ◽  
Topographic Map ◽  
Texture Information ◽  
Occurrence Matrix

The growing availability of the satellite data has augmented the need of information extraction that can be utilized in various application including topographic map updation, city planning, pattern recognition and machine vision etc. The accurate information extraction from satellite images involves the integration of additional measures such as texture, shape etc. In this paper, investigation on extraction of topographic objects from satellite images by incorporating the texture information and data fusion has been made. The applicability of various texture measures based on the gray level co-occurrence matrix along with the effect of varying pixel window is also discussed. The classification results indicate that homogeneity texture image generated using 3*3 window size is best suitable for topographic objects extraction. The best classification results with overall accuracy 85.0% and kappa coefficient 0.80 are obtained when classification is performed on fused image (Multispectral + PAN + Texture).

scholarly journals ERRATUM

2014 ◽  
Vol 40 (4) ◽  
pp. EBI-EBI
Author(s):  
Kuldeep Chaurasia ◽  
Pradeep Kumar Garg
Keyword(s):  
Data Fusion ◽  
Satellite Data ◽  
Texture Information

"Erratum on the article ‘The role of texture information and data fusion in topographic objects extraction from satellite data’" Geodesy and Cartography.

scholarly journals Adopting Image Integration Techniques to Simulate Satellite Images

2020 ◽  
pp. 3445-3455
Author(s):  
Heba Khudhair Abbas ◽  
Farah Faris ◽  
Sale Sami ◽  
Al Zahraa Fadel
Keyword(s):  
Satellite Images ◽  
Signal To Noise Ratio ◽  
Accurate Information ◽  
Integration Process ◽  
Image Region ◽  
Contrast Measure ◽  
Integration Techniques ◽  
Mathematical Relationships ◽  
Nearest Neighborhood

Mathematical integration techniques rely on mathematical relationships such as addition, subtraction, division, and subtraction to merge images with different resolutions to achieve the best effect of the merger. In this study, a simulation is adopted to correct the geometric and radiometric distortion of satellite images based on mathematical integration techniques, including Brovey Transform (BT), Color Normalization Transform (CNT), and Multiplicative Model (MM). Also, interpolation methods, namely the nearest neighborhood, Bi-linear, and Bi-cubic were adapted to the images captured by an optical camera. The evaluation of images resulting from the integration process was performed using several types of measures; the first type depends on the determination of quality in the regions of the edges using a contrast measure as well as the number of edges and threshold. The second type is the global one that is based on the parameters of the image region, including the Mean (µ), Standard Deviation (SD), and Signal to Noise Ratio (SNR). The parameters also included the Amount of Information Added (AIA) to the original image, such as those for the total (AIAt) , edges (AIAe), and homogenous (AIAh) regions. The results showed the efficiency of the integration process in the image fusion with different resolutions in one image integrated resolution. The quality measures used were also capable in evaluating the most efficient techniques and determining the accurate information of the resulting image.

Investigation of coastal morphological changes due to river basin characteristics by means of remote sensing and GIS techniques

2003 ◽  
Vol 48 (10) ◽  
pp. 135-142 ◽  
Author(s):  
D.Z. Seker ◽  
C. Goksel ◽  
S. Kabdasli ◽  
N. Musaoglu ◽  
S. Kaya
Keyword(s):  
Black Sea ◽  
Satellite Data ◽  
Satellite Images ◽  
Sandy Beach ◽  
Morphological Changes ◽  
Remote Sensing And Gis ◽  
The Black Sea ◽  
Black Sea Coast ◽  
Delta Formation ◽  
Bathymetric Changes

The Riva River is located on the Anatolian (Asian) side of Istanbul by the Black Sea coast, with a wonderful sandy beach and delta formation which has been selected as the study area. The Riva is the largest river in this region, which flows into the Black Sea and also gives its’ name to the area. The river carries some amount of sediments to the Black Sea. These particles cause considerable changes not only in the bed bathymetry and coastal boundaries of the river but also along the coastline of the Black Sea. The aim of this study is to determine these variations by means of satellite data and GIS. In the study, satellite images dated 1975, 1984, 1992 and 2001 have been used. At the end of the study, the possibility of observing bathymetric changes in front of the coastline by means of satellite data has been investigated and results were evaluated and visualised by means of GIS.

scholarly journals Integrated satellite data fusion and mining for monitoring lake water quality status of the Albufera de Valencia in Spain

2015 ◽  
Vol 151 ◽  
pp. 416-426 ◽  
Author(s):  
Carolina Doña ◽  
Ni-Bin Chang ◽  
Vicente Caselles ◽  
Juan M. Sánchez ◽  
Antonio Camacho ◽  
...  
Keyword(s):  
Water Quality ◽  
Data Fusion ◽  
Satellite Data ◽  
Lake Water ◽  
Lake Water Quality ◽  
Water Quality Status ◽  
Quality Status

Image Retrieval Using Intensity Gradients and Texture Chromatic Pattern

2021 ◽  
Vol 17 (1) ◽  
pp. 57-73
Author(s):  
I.Jeena Jacob ◽  
Betty Paulraj ◽  
P. Ebby Darney ◽  
Hoang Viet Long ◽  
Tran Manh Tuan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Satellite Images ◽  
Local Binary Pattern ◽  
Texture Feature ◽  
Query Image ◽  
Shape Information ◽  
Histogram Of Oriented Gradient ◽  
Texture Pattern ◽  
Texture Information

Methods to retrieve images involve retrieving images from the database by using features of it. They are colour, shape, and texture. These features are used to find the similarity for the query image with that of images in the database. The images are sorted in the order with this similarity. The article uses intra- and inter-texture chrominance and its intensity. Here inter-chromatic texture feature is extracted by LOCTP (local oppugnant colored texture pattern). Local binary pattern (LBP) gives the intra-texture information. Histogram of oriented gradient (HoG) is used to get the shape information from the satellite images. The performance analysis is land-cover remote sensing database, NWPU-VHR-10 dataset, and satellite optical land cover database gives better results than the previous works.

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