Remote Sensing Commons^™

Land Target Detection Algorithm In Remote Sensing Images Based On Deep Learning, Wenyi Hu, Xiaomeng Jiang, Jiawei Tian, Shitong Ye, Shan Liu

Electrical & Computer Engineering Faculty Publications

Remote sensing technology plays a crucial role across various sectors, such as meteorological monitoring, city planning, and natural resource exploration. A critical aspect of remote sensing image analysis is land target detection, which involves identifying and classifying land-based objects within satellite or aerial imagery. However, despite advancements in both traditional detection methods and deep-learning-based approaches, detecting land targets remains challenging, especially when dealing with small and rotated objects that are difficult to distinguish. To address these challenges, this study introduces an enhanced model, YOLOv5s-CACSD, which builds upon the YOLOv5s framework. Our model integrates the channel attention (CA) mechanism, CARAFE, and …

Atmospheric Turbulence Distortion In Video: Restoration Utilizing Sparse Analysis, Benjamin J. Sanda

Dissertations

The removal of atmospheric turbulence (AT) distortion in long range imaging is one of the most challenging areas of research in imaging processing with an immediate need for solutions in several applications such as in military and transportation systems. AT exacerbates distortion due to non-linear geometric blur and scintillations in long-distance images and videos, severely reducing image quality and information interpretation. AT negatively impacts both human and computer vision systems, compromising visibility essential for accurate object identification and tracking.

In this dissertation, a novel sparse analysis framework is developed to address efficient AT blur and scintillation removal in video. Operating …

Deep Learning For Remote Sensing Image Processing, Yan Lu

Computational Modeling & Simulation Engineering Theses & Dissertations

Remote sensing images have many applications such as ground object detection, environmental change monitoring, urban growth monitoring and natural disaster damage assessment. As of 2019, there were roughly 700 satellites listing “earth observation” as their primary application. Both spatial and temporal resolutions of satellite images have improved consistently in recent years and provided opportunities in resolving fine details on the Earth's surface. In the past decade, deep learning techniques have revolutionized many applications in the field of computer vision but have not fully been explored in remote sensing image processing. In this dissertation, several state-of-the-art deep learning models have been …

Cross Calibration And Validation Of Landsat 8 Oli And Sentinel 2a Msi, M. M. Farhad

Electronic Theses and Dissertations

This work describes a proposed radiometric cross calibration between the Landsat 8 Operational Land Imager (OLI) and Sentinel 2A Multispectral Instrument (MSI) sensors. The cross calibration procedure involves i) correction of the MSI data to account for spectral band differences with the OLI; and ii) correction of BRDF effects in the data from both sensors using a new model accounting for the view zenith/azimuth angles in addition to the solar zenith/view angles. Following application of the spectral and BRDF corrections, standard least-squares linear regression is used to determine the cross calibration gain and offset in each band. Uncertainties related to …

Remote Sensing Of Hidden Objects, Mark G. Hoelscher, Michael A. Marciniak

AFIT Patents

An apparatus and method are provided for creating an indirect image of an object. The apparatus includes a light source and an imaging system. Light emitted from the light source is reflected by a first non-specular surface toward the object. Light reflected by the object is further reflected by a second non-specular surface toward the imaging system. The imaging system is configured to create the indirect image from the reflected light.

Background And Study Concerning Water Wave Effects On Airborne Imagery, Charles R. Bostater

Ocean Engineering and Marine Sciences Faculty Publications

This paper describes ongoing research and initial results regarding collection of airborne imagery for detection of submerged features in optically shallow water types. The approach is to utilize land surface, water surface and submerged or in-situ line targets of various types during the airborne flights or fixed platforms. The imagery collected by the airborne sensing systems is processed in concept to correct for the presence of the water surface wave effects and water column effects. The correction approach is based upon calculation of a residual image between either (a) the observed submerged target image and the non-submerged image or (2) …

Aerial And Satellite Image Processing Applications, Srinivas K. Jakkula

Electrical & Computer Engineering Theses & Dissertations

Aerial and satellite images are used extensively in many trip and mapping software packages, such as Google Earth etc. Aerial images differ significantly due to the variations in atmospheric clarity, atmospheric layer density, humidity, temperature, and season under which the aerial images are captured. Among the issues in effective utilization of aerial images, color tone discrepancy is the inconsistency in brightness, saturation, or color balance between images representing adjacent areas, causing adjacent areas appear significantly different that would otherwise be similar. Aenal images are also routinely used as ground textures to simulate Earth surface and 3D features on Earth in …

Optimal Band Selection For Hyperspectral Remote Sensing Of Aquatic Benthic Features - A Wavelet Filter Window Approach, Charles R. Bostater

Ocean Engineering and Marine Sciences Faculty Publications

This paper describes a wavelet based approach to derivative spectroscopy. The approach is utilized to select, through optimization, optimal channels or bands to use as derivative based remote sensing algorithms. The approach is applied to airborne and modeled or synthetic reflectance signatures of environmental media and features or objects within such media, such as benthic submerged vegetation canopies. The technique can also applied to selected pixels identified within a hyperspectral image cube obtained from an board an airborne, ground based, or subsurface mobile imaging system. This wavelet based image processing technique is an extremely fast numerical method to conduct higher …

Methods For Correcting Topographically Induced Radiometric Distortion On Landsat Thematic Mapper Images For Land Cover Classification, David Michael Rosen

Geography Masters Research Papers

Satellite imagery is commonly used to study land-use, land-cover change in mountainous areas. Classification of land-cover types is particularly difficult in this type of terrain because topography affects the spectral response of surface features. Several techniques have been developed to help compensate for this topographic effect and to increase classification accuracy.

The purpose of this study is to compare topographic correction methods to determine which produces the most accurate results. Method 1 does not use any topographic correction, serving as a control. Method 2 is based on the Lambertian model, and uses topographical data as variables in an equation. Method …

Binary Programming Models Of Spatial Pattern Recognition: Applications In Remote Sensing Image Analysis, Thomas G. Reed

Theses and Dissertations

The major purpose of this investigation was to implement subregion allocation objectives using a network model base on an existing subregion allocation binary programming model (Benabdallah and Wright (B&W), 1990), the ultimate goal being the application of subregion allocation concepts towards the spatial analysis of satellite imagery. The multi-objective aspects of subregion allocation can be accomplished via a network formulation, a formulation vastly simpler in complexity than the binary programming models previously used. Without a network programming package that could maintain integral flows, however, deriving the solution was a tiresome task for the user. Nonetheless, several new concepts and advantages …

Wind Streamline Ambiguity Removal Of Microwave Scatterometer Data, Hans W. Zaepfel

Electrical & Computer Engineering Theses & Dissertations

There is a class of satellite microwave scatterometers that return oceanographic information which includes wind vectors with directional ambiguity. The first part of the ambiguity removal process is to reduce the data to a directional ambiguity of 180°. This thesis shows that wind direction change contains the information required for streamline ambiguity removal and that syntactic pattern recognition techniques can be used to locate the areas of wind direction change. Spreading the information along the areas of wind direction change results in the removal of the streamline ambiguity. The algorithm is implemented and the results are presented showing that it …