scholarly journals Comparison of Various Frequency Matching Schemes for Geometric Correction of Geostationary Ocean Color Imager

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5564
Author(s):  
Jong-Hwan Son ◽  
Han-Gyeol Kim ◽  
Hee-Jeong Han ◽  
Taejung Kim
Keyword(s):  
Frequency Domain ◽  
Ocean Color ◽  
Phase Correlation ◽  
Range Limits ◽  
Geometric Correction ◽  
Matching Method ◽  
Search Range ◽  
Frequency Matching ◽  
Matching Technique ◽  
Matching Schemes

Current precise geometric correction of Geostationary Ocean Color Imager (GOCI) image slots is performed by shoreline matching. However, it is troublesome to handle slots with few or no shorelines, or slots covered by clouds. Geometric correction by frequency matching has been proposed to handle these slots. In this paper, we further extend previous research on frequency matching by comparing the performance of three frequency domain matching methods: phase correlation, gradient correlation, and orientation correlation. We compared the performance of each matching technique in terms of match success rate and geometric accuracy. We concluded that the three frequency domain matching method with peak search range limits was comparable to geometric correction performance with shoreline matching. The proposed method handles translation only, and assumes that rotation has been corrected. We need to do further work on how to handle rotation by frequency matching.

scholarly journals AUTOMATED MOSAICKING OF GEOSTATIONARY OCEAN COLOR IMAGER BY COMBINATION OF SPATIAL AND FREQUENCY MATCHING

2018 ◽  
Vol XLII-2 ◽  
pp. 495-499
Author(s):  
H. G. Kim ◽  
J. H. Son ◽  
T. Kim
Keyword(s):  
Frequency Domain ◽  
Spatial Domain ◽  
Geometric Distortion ◽  
Future Research ◽  
Geometric Correction ◽  
Frequency Matching ◽  
Image Mosaicking ◽  
Important Processing ◽  
Sensor Modelling

In general, image mosaicking is a useful and important processing for handling images with narrow field of view. It is being used widely for images from commercial cameras as well as from aerial and satellite cameras. For mosaicking images with geometric distortion, geometric correction of each image should be performed before combining images. However, automated mosaicking images with geometric distortion is not a trivial task. The goal of this paper is the development of automated mosaicking techniques applicable to handle GOCI images. In this paper, we try to extract tie-points by using spatial domain and frequency domain matching and perform the mosaicking of GOCI. The method includes five steps. First, we classify GOCI image slots according to the existence of shorelines by spatial domain matching. Second, we perform precise geometric correction on the slots with shorelines. Third, we perform initial sensor modelling for the slots without shorelines and apply geometric correction based on the initial model. Fourth, the relative relationship between the slots without shorelines and the slots with shorelines is estimated through frequency domain matching. Lastly, mosaicking of geometrically corrected all 16 image slots is performed. The proposed method was verified by applying to real GOCI images. The proposed method was able to perform automated mosaicking even for images without shorelines, and its accuracy and processing time were satisfactory. For future research, we will improve frequency matching to generate multiple tie-points and to analyse the applicability of precise sensor modelling directly from frequency matching. It is expected that the proposed method can be applied to the follow-up sensor of the GOCI, GOCI-II, and other ocean satellite images.

scholarly journals Geometric Correction for the Geostationary Ocean Color Imager from a Combination of Shoreline Matching and Frequency Matching

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3599 ◽  
Author(s):  
Han-Gyeol Kim ◽  
Jong-Hwan Son ◽  
Taejung Kim
Keyword(s):  
Ocean Color ◽  
Correction Method ◽  
Relative Orientation ◽  
Geometric Distortion ◽  
Geometric Correction ◽  
Frequency Matching ◽  
Sensor Model ◽  
Color Sensors ◽  
Similar Accuracy ◽  
Sensor Modeling

Geometric correction is fundamental in producing high quality satellite data products. However, the geometric correction for ocean color sensors, e.g., Geostationary Ocean Color Imager (GOCI), is challenging because the traditional method based on ground control points (GCPs) cannot be applied when the shoreline is absent. In this study, we develop a hybrid geometric correction method, which applies shoreline matching and frequency matching on slots with shorelines and without shorelines, respectively. Frequency matching has been proposed to estimate the relative orientation between GOCI slots without a shoreline. In this paper, we extend our earlier research for absolute orientation and geometric correction by combining frequency matching results with shoreline matching ones. The proposed method consists of four parts: Initial sensor modeling of slots without shorelines, precise sensor modeling through shoreline matching, relative orientation modeling by frequency matching, and generation of geometric correction results using a combination of the two matching procedures. Initial sensor modeling uses the sensor model equation for GOCI and metadata in order to remove geometric distortion due to the Earth’s rotation and curvature in the slots without shorelines. Precise sensor modeling is performed with shoreline matching and random sample consensus (RANSAC) in the slots with shorelines. Frequency matching computes position shifts for slots without shorelines with respect to the precisely corrected slots with shorelines. GOCI Level 1B scenes are generated by combining the results from shoreline matching and frequency matching. We analyzed the accuracy of shoreline matching alone against that of the combination of shoreline matching and frequency matching. Both methods yielded a similar accuracy of 1.2 km, which supports the idea that frequency matching can replace traditional shoreline matching for slots without visible shorelines.

scholarly journals Improving of Data Processing Effectiveness for Pavement Structural Evaluation Using Subsurface Radar Probing

2013 ◽  
Vol 14 (2) ◽  
pp. 143-154
Author(s):  
Alexander Krainyukov ◽  
Valery Kutev
Keyword(s):  
Genetic Algorithm ◽  
Inverse Problem ◽  
Data Processing ◽  
Frequency Domain ◽  
Iterative Procedure ◽  
Search Range ◽  
Structural Evaluation ◽  
Modified Genetic Algorithm ◽  
Pavement Structure ◽  
Structure Evaluation

Problems of the data processing improving for pavement structure evaluation with help of subsurface radar probing are discussed. Iterative procedure to solve the inverse problem in frequency domain is used on the base of the genetic algorithm. For improving of data processing effectiveness it is proposed to use a modified genetic algorithm with adaptation of search range of pavement parameters. The results of reconstruction of electro-physical characteristics for model of five-layered pavement structure are presented.

Dual-Broadband Impedance Converter Based on Multiedge Frequency Matching Technique

2021 ◽  
pp. 1-4
Author(s):  
Cuiping Yu ◽  
Xincheng Ma ◽  
Xiangyu Meng ◽  
Yuanan Liu ◽  
Xiangyang Duan
Keyword(s):  
Frequency Matching ◽  
Matching Technique ◽  
Impedance Converter

Complete Pattern Matching for DNA Computing

2006 ◽  
Vol 05 (04) ◽  
pp. 337-343
Author(s):  
Nadia Nedjah ◽  
Luiza De Macedo Mourelle
Keyword(s):  
Information Retrieval ◽  
Logic Programming ◽  
Pattern Matching ◽  
Theorem Proving ◽  
Dna Computing ◽  
Term Rewriting ◽  
Matching Method ◽  
Subject Term ◽  
Matching Technique ◽  
Complete Matching

Pattern matching is essential in many applications such as information retrieval, logic programming, theorem-proving, term rewriting and DNA-computing. It usually breaks down into two categories: root and complete pattern matching. Root matching determines whether a subject term is an instance of a pattern in a pattern set while complete matching determines whether a subject term contains a sub-term that is an instance of a pattern in a pattern set. For the sake of efficiency, root pattern matching need to be deterministic and lazy. Furthermore, complete pattern matching also needs to be parallel. Unlike root pattern matching, complete matching received little interest from the researchers of the field. In this paper, we present a novel deterministic multi-threaded complete matching method. This method subsumes a deterministic lazy root matching technique that was developped by the authors in an earlier work. We evaluate the performance of proposed method using theorem-proving and DNA-computing applications.

Sign in / Sign up

Export Citation Format

Share Document