Image Processing and Data Analysis with ERDAS IMAGINE

Purpose The purpose of this paper is to discuss unmanned aerial vehicle (UAV) and the comparison of image processing software. Design/methodology/approach Images from a drone are used and processed with new digital image processing software, Imagine UAV® of Erdas imagine 2015®. The products (Digital Surface Model and ortho images) are validated with check points (CPs) measured in the field with Global Positioning System. Moreover, similar products are produced by Agisoft PhotoScan® software and are compared with both the products of Imagine UAV and the CPs. Findings The results reveal that the two software tools are almost equivalent, while the accuracies of their products are similar to the accuracies of the external orientations of drone images. Originality/value Comparison of image processing software.

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Application of Big Data Analysis and Image Processing Technology in Athletes Training Based on Intelligent Machine Vision Technology

10.1007/978-981-16-5857-0_87 ◽

2021 ◽

pp. 687-693

Author(s):

Juan Zhong ◽

Bo He

Keyword(s):

Image Processing ◽

Big Data ◽

Data Analysis ◽

Machine Vision ◽

Big Data Analysis ◽

Processing Technology ◽

Intelligent Machine ◽

Image Processing Technology

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Comparative Study of Change Detection and Urban Expansion Using Multi-Date Multi-Source Data: A Case Study of Greater Khartoum

Journal of King Abdulaziz University-Engineering Sciences ◽

10.4197/eng.23-2.8 ◽

2012 ◽

Vol 23 (2) ◽

pp. 139-172

Author(s):

Abdullah Salman Alsalman Abdullah Salman Alsalman

Keyword(s):

Image Processing ◽

Change Detection ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Urban Expansion ◽

Remote Sensing Data ◽

Principal Component ◽

Test Area ◽

Image Differencing ◽

Erdas Imagine

Noting that Khartoum represents the most rapidly expanding city in the Sudan and taking into account that change detection operations are seldom , the present study has been initiated to attempt to produce work that synthesizes land use/land cover (LULC) to investigate change detection using GIS, remote sensing data and digital image processing techniques; estimate, evaluate and map changes that took place in the city from 1975 to 2003. The experiment used the techniques of visual inspection, write-function-memoryinsertion, image differencing, image transformation i.e. normalized difference vegetation index (NDVI), tasseled cap, principal component analysis (PCA), post-classification comparison and GIS. The results of all these various techniques were used by the authors to study change detection of the geographic locale of the test area. Image processing and GIS techniques were performed using Intergraph Image analyst 8.4 and GeoMedia professional version 6, ERDAS Imagine 8.7, and ArcGIS 9.2. Results obtained were discussed and analyzed in a comparative manner and a conclusion regarding the best method for change detection of the test area was derived.

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