Sensor resolution enhancement for remote imaging by synthesizing mask-based camera array images

2018 ◽  
Vol 25 (6) ◽  
pp. 708-719
Author(s):  
Zhuang Ma ◽  
Zhaofeng Cen ◽  
Xiaotong Li
1998 ◽  
Author(s):  
Milos Sobotka ◽  
Ivan Prochazka ◽  
Karel Hamal ◽  
Josef Blazej

Author(s):  
J.K. Weiss ◽  
M. Gajdardziska-Josifovska ◽  
M. R. McCartney ◽  
David J. Smith

Interfacial structure is a controlling parameter in the behavior of many materials. Electron microscopy methods are widely used for characterizing such features as interface abruptness and chemical segregation at interfaces. The problem for high resolution microscopy is to establish optimum imaging conditions for extracting this information. We have found that off-axis electron holography can provide useful information for the study of interfaces that is not easily obtained by other techniques.Electron holography permits the recovery of both the amplitude and the phase of the image wave. Recent studies have applied the information obtained from electron holograms to characterizing magnetic and electric fields in materials and also to atomic-scale resolution enhancement. The phase of an electron wave passing through a specimen is shifted by an amount which is proportional to the product of the specimen thickness and the projected electrostatic potential (ignoring magnetic fields and diffraction effects). If atomic-scale variations are ignored, the potential in the specimen is described by the mean inner potential, a bulk property sensitive to both composition and structure. For the study of interfaces, the specimen thickness is assumed to be approximately constant across the interface, so that the phase of the image wave will give a picture of mean inner potential across the interface.


2010 ◽  
Author(s):  
Alan R. Pinkus ◽  
David W. Dommett ◽  
H. L. Task ◽  
Sheldon E. Unger ◽  
David W. Sivert
Keyword(s):  

2021 ◽  
Vol 13 (6) ◽  
pp. 3246
Author(s):  
Zoe Slattery ◽  
Richard Fenner

Building on the existing literature, this study examines whether specific drivers of forest fragmentation cause particular fragmentation characteristics, and how these characteristics can be linked to their effects on forest-dwelling species. This research uses Landsat remote imaging to examine the changing patterns of forests. It focuses on areas which have undergone a high level of a specific fragmentation driver, in particular either agricultural expansion or commodity-driven deforestation. Seven municipalities in the states of Rondônia and Mato Grosso in Brazil are selected as case study areas, as these states experienced a high level of commodity-driven deforestation and agricultural expansion respectively. Land cover maps of each municipality are created using the Geographical Information System software ArcGIS Spatial Analyst extension. The resulting categorical maps are input into Fragstats fragmentation software to calculate quantifiable fragmentation metrics for each municipality. To determine the effects that these characteristics are likely to cause, this study uses a literature review to determine how species traits affect their responses to forest fragmentation. Results indicate that, in areas that underwent agricultural expansion, the remaining forest patches became more complex in shape with longer edges and lost a large amount of core area. This negatively affects species which are either highly dispersive or specialist to core forest habitat. In areas that underwent commodity-driven deforestation, it was more likely that forest patches would become less aggregated and create disjunct core areas. This negatively affects smaller, sedentary animals which do not naturally travel long distances. This study is significant in that it links individual fragmentation drivers to their landscape characteristics, and in turn uses these to predict effects on species with particular traits. This information will prove useful for forest managers, particularly in the case study municipalities examined in this study, in deciding which species require further protection measures. The methodology could be applied to other drivers of forest fragmentation such as forest fires.


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