Phase Correlation Decomposition: The Impact of Illumination Variation for Robust Subpixel Remotely Sensed Image Matching

2019 ◽  
Vol 57 (9) ◽  
pp. 6710-6725 ◽  
Author(s):  
Xue Wan ◽  
Jian Guo Liu ◽  
Shengyang Li ◽  
Hongshi Yan
Keyword(s):  
Image Matching ◽  
Remotely Sensed ◽  
Phase Correlation ◽  
Illumination Variation ◽  
Remotely Sensed Image ◽  
The Impact

scholarly journals Phase Correlation based Local Illumination-invariant Method for Multi-Tempro Remote Sensing Image Matching

2014 ◽  
Vol XL-3 ◽  
pp. 365-372 ◽  
Author(s):  
X. Wan ◽  
J. Liu ◽  
H. Yan
Keyword(s):  
Image Matching ◽  
Phase Correlation ◽  
Disparity Estimation ◽  
Image Alignment ◽  
Disparity Map ◽  
Illumination Variation ◽  
Illumination Invariant ◽  
Lighting Conditions ◽  
Local Illumination ◽  
Solar Position

This paper aims at image matching under significantly different illumination conditions, especially illumination angle changes, without prior knowledge of lighting conditions. We investigated the illumination impact on Phase Correlation (PC) matrix by mathematical derivation and from which, we decomposed PC matrix as the multiplication product of the illumination impact matrix and the translation matrix. Thus the robustness to illumination variation of the widely used Absolute Dirichlet Curve-fitting (AD-CF) algorithm for pixel-wise disparity estimation is proved. Further, an improved PC matching algorithm is proposed: Absolute Dirichlet SVD (AD-SVD), to achieve illumination invariant image alignment. Experiments of matching DEM simulated terrain shading images under very different illumination angles demonstrated that AD-SVD achieved 1/20 pixels accuracy for image alignment and it is nearly entirely invariant to daily and seasonal solar position variation. The AD-CF algorithm was tested for generating disparity map from multi-illumination angle stereo pairs and the results demonstrated high fidelity to the original DEM and the Normalised Correlation Coefficient (NCC) between the two is 0.96.

scholarly journals A Subpixel Matching Method for Stereovision of Narrow Baseline Remotely Sensed Imagery

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Ning Ma ◽  
Peng-fei Sun ◽  
Yu-bo Men ◽  
Chao-guang Men ◽  
Xiang Li
Keyword(s):  
Image Matching ◽  
Remotely Sensed ◽  
Phase Correlation ◽  
Disparity Estimation ◽  
Matching Method ◽  
Remotely Sensed Imagery ◽  
Novel Variant ◽  
Remotely Sensed Images ◽  
Relationship Of ◽  
The Relationship

In this paper, an accurate and efficient image matching method based on phase correlation is proposed to estimate disparity with subpixel precision, which is used for the stereovision of narrow baseline remotely sensed images. The multistep strategy is adopted in our technical frame; thus the disparity estimation is divided into two steps: integer-pixel prematching and subpixel matching. Firstly, integer-pixel disparity is estimated by employing a cross-based local matching method. Then the relationship of corresponding points is established under the guidance of integer-pixel disparity. The subimages are extracted through selecting the corresponding points as the center. Finally, the subpixel disparity is obtained by matching the subimages utilizing a novel variant of phase correlation approach. The experiment results show that the proposed method can match different kinds of large-sized narrow baseline remotely sensed images and estimate disparity with subpixel precision automatically.

scholarly journals ILLUMINATION INVARIANT CHANGE DETECTION (IICD): FROM EARTH TO MARS

2018 ◽  
Vol XLII-3 ◽  
pp. 1673-1680
Author(s):  
X. Wan ◽  
J. Liu ◽  
M. Qin ◽  
S. Y. Li
Keyword(s):  
Change Detection ◽  
Image Matching ◽  
Large Scale ◽  
Satellite Images ◽  
Environmental Changes ◽  
Phase Correlation ◽  
Small Object ◽  
Illumination Variation ◽  
Illumination Invariant ◽  
Multi Temporal

Multi-temporal Earth Observation and Mars orbital imagery data with frequent repeat coverage provide great capability for planetary surface change detection. When comparing two images taken at different times of day or in different seasons for change detection, the variation of topographic shades and shadows caused by the change of sunlight angle can be so significant that it overwhelms the real object and environmental changes, making automatic detection unreliable. An effective change detection algorithm therefore has to be robust to the illumination variation. This paper presents our research on developing and testing an Illumination Invariant Change Detection (IICD) method based on the robustness of phase correlation (PC) to the variation of solar illumination for image matching.<br> The IICD is based on two key functions: i) initial change detection based on a saliency map derived from pixel-wise dense PC matching and ii) change quantization which combines change type identification, motion estimation and precise appearance change identification. Experiment using multi-temporal Landsat 7 ETM+ satellite images, Rapid eye satellite images and Mars HiRiSE images demonstrate that our frequency based image matching method can reach sub-pixel accuracy and thus the proposed IICD method can effectively detect and precisely segment large scale change such as landslide as well as small object change such as Mars rover, under daily and seasonal sunlight changes.

scholarly journals Predicting distribution of malaria vector larval habitats in Ethiopia by integrating distributed hydrologic modeling with remotely sensed data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ai-Ling Jiang ◽  
Ming-Chieh Lee ◽  
Guofa Zhou ◽  
Daibin Zhong ◽  
Dawit Hawaria ◽  
...  
Keyword(s):  
Malaria Vector ◽  
Malaria Control ◽  
Remotely Sensed ◽  
Larval Habitat ◽  
Validation Dataset ◽  
Significant Shift ◽  
Remotely Sensed Data ◽  
Larval Habitats ◽  
Common Land Model ◽  
The Impact

AbstractLarval source management has gained renewed interest as a malaria control strategy in Africa but the widespread and transient nature of larval breeding sites poses a challenge to its implementation. To address this problem, we propose combining an integrated high resolution (50 m) distributed hydrological model and remotely sensed data to simulate potential malaria vector aquatic habitats. The novelty of our approach lies in its consideration of irrigation practices and its ability to resolve complex ponding processes that contribute to potential larval habitats. The simulation was performed for the year of 2018 using ParFlow-Common Land Model (CLM) in a sugarcane plantation in the Oromia region, Ethiopia to examine the effects of rainfall and irrigation. The model was calibrated using field observations of larval habitats to successfully predict ponding at all surveyed locations from the validation dataset. Results show that without irrigation, at least half of the area inside the farms had a 40% probability of potential larval habitat occurrence. With irrigation, the probability increased to 56%. Irrigation dampened the seasonality of the potential larval habitats such that the peak larval habitat occurrence window during the rainy season was extended into the dry season. Furthermore, the stability of the habitats was prolonged, with a significant shift from semi-permanent to permanent habitats. Our study provides a hydrological perspective on the impact of environmental modification on malaria vector ecology, which can potentially inform malaria control strategies through better water management.

Characterization of pasture biophysical properties and the impact of grazing intensity using remotely sensed data

2007 ◽  
Vol 109 (3) ◽  
pp. 314-327 ◽  
Author(s):  
Izaya Numata ◽  
Dar A. Roberts ◽  
Oliver A. Chadwick ◽  
Josh Schimel ◽  
Fernando R. Sampaio ◽  
...  
Keyword(s):  
Grazing Intensity ◽  
Remotely Sensed ◽  
Biophysical Properties ◽  
Remotely Sensed Data ◽  
The Impact

scholarly journals Remotely Sensed Image Classification Using Sparse Representations of Morphological Attribute Profiles

2014 ◽  
Vol 52 (8) ◽  
pp. 5122-5136 ◽  
Author(s):  
Benqin Song ◽  
Jun Li ◽  
Mauro Dalla Mura ◽  
Peijun Li ◽  
Antonio Plaza ◽  
...  
Keyword(s):  
Image Classification ◽  
Remotely Sensed ◽  
Sparse Representations ◽  
Remotely Sensed Image ◽  
Morphological Attribute

A microcomputer system for remotely sensed image data on ecological environments

1986 ◽  
Vol 32 (1-3) ◽  
pp. 15-27
Author(s):  
Yuzo Suga ◽  
Tanehiro Futagami ◽  
Kaneo Okano ◽  
Sotaro Tanaka ◽  
Toshiro Sugimura
Keyword(s):  
Image Data ◽  
Remotely Sensed ◽  
Microcomputer System ◽  
Remotely Sensed Image

scholarly journals Exceptional retreat of Novaya Zemlya's marine-terminating outlet glaciers between 2000 and 2013

2017 ◽  
Author(s):  
J. Rachel Carr ◽  
Heather Bell ◽  
Rebecca Killick ◽  
Tom Holt
Keyword(s):  
Sea Ice ◽  
Sea Level Rise ◽  
Sea Level ◽  
Remotely Sensed ◽  
Glacier Retreat ◽  
Remotely Sensed Data ◽  
Novaya Zemlya ◽  
The Past ◽  
Air Temperatures ◽  
The Impact

Abstract. Novaya Zemlya (NVZ) has experienced rapid ice loss and accelerated marine-terminating glacier retreat during the past two decades. However, it is unknown whether this retreat is exceptional longer-term and/or whether it has persisted since 2010. Investigating this is vital, as dynamic thinning may contribute substantially to ice loss from NVZ, but is not currently included in sea level rise predictions. Here, we use remotely sensed data to assess controls on NVZ glacier retreat between the 1973/6 and 2015. Glaciers that terminate into lakes or the ocean receded 3.5 times faster than those that terminate on land. Between 2000 and 2013, retreat rates were significantly higher on marine-terminating outlet glaciers than during the previous 27 years, and we observe widespread slow-down in retreat, and even advance, between 2013 and 2015. There were some common patterns in the timing of glacier retreat, but the magnitude varied between individual glaciers. Rapid retreat between 2000–2013 corresponds to a period of significantly warmer air temperatures and reduced sea ice concentrations, and to changes in the NAO and AMO. We need to assess the impact of this accelerated retreat on dynamic ice losses from NVZ, to accurately quantify its future sea level rise contribution.

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