scholarly journals An Operational Tool for the Automatic Detection and Removal of Border Noise in Sentinel-1 GRD Products

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3454 ◽  
Author(s):  
Mattia Stasolla ◽  
Xavier Neyt
Keyword(s):  
Mathematical Morphology ◽  
Entire Range ◽  
Automatic Detection ◽  
New Method ◽  
Numerical Assessment ◽  
Acquisition Mode ◽  
Operational Tool

The presence of border noise in Sentinel-1 Ground Range Detected (GRD) products is an undesired processing artifact that limits their full exploitation in a number of applications. All of the Sentinel-1 GRD products generated before March 2018—more than 800,000—are affected by this particular type of noise. In March 2018, an official fix was deployed that solved the problem for a large portion of the newly generated products, but it did not cover the entire range of products, hence the need for an operational tool that is able to effectively and consistently remove border noise in an automated way. Currently, a few solutions have been proposed that try to address the problem, but all of them have limitations. The scope of this paper is therefore to present a new method based on mathematical morphology for the automatic detection and masking of border noise in Sentinel-1 GRD products that is able to overcome the existing limitations. To evaluate the performance of the method, a detailed numerical assessment was carried out, using, as a benchmark, the ‘Remove GRD Border Noise’ module integrated in ESA’s Sentinel Application Platform. The results showed that the proposed method is capable of very accurately removing the undesired noisy pixels from GRD images, regardless of their acquisition mode, polarization, or resolution and can cope with challenging features within the image scenes that typically affect other approaches.

Image Retrieval Based on Edge Detection and Histogram

2012 ◽  
Vol 157-158 ◽  
pp. 1038-1041
Author(s):  
Wei Dong ◽  
Yan Dong Tang
Keyword(s):  
Edge Detection ◽  
Image Retrieval ◽  
Mathematical Morphology ◽  
Paper Analysis ◽  
Experimental Results ◽  
New Method

Based on the existing algorithm, improved mathematical morphology for image retrieval, a new method, using the combination of edge magnitude histogram and edge angular histogram, was proposed in this paper. Analysis and experimental results reveal that the proposed algorithm has a superior image retrieving performance.

scholarly journals A new method for vehicles detection and tracking using information and image processing

2021 ◽  
Vol 11 (6) ◽  
pp. 4942
Author(s):  
Mazouzi Amine ◽  
Kerfa Djoudi ◽  
Ismail Rakip Karas
Keyword(s):  
Image Processing ◽  
Mathematical Morphology ◽  
New Method ◽  
Video Sequences ◽  
Detection Level ◽  
Low Level ◽  
Detection And Tracking ◽  
High Level

<span lang="EN-US">In this article, a new method of vehicles detecting and tracking is presented: A thresholding followed by a mathematical morphology treatment are used. The tracking phase uses the information about a vehicle. An original labeling is proposed in this article. It helps to reduce some artefacts that occur at the detection level. The main contribution of this article lies in the possibility of merging information of low level (detection) and high level (tracking). In other words, it is shown that many artefacts resulting from image processing (low level) can be detected, and eliminated thanks to the information contained in the labeling (high level). The proposed method has been tested on many video sequences and examples are given illustrating the merits of our approach.</span>

A new method for the analysis of fire spread modeling errors

2002 ◽  
Vol 11 (4) ◽  
pp. 193 ◽  
Author(s):  
Francis M. Fujioka
Keyword(s):  
Probability Model ◽  
Weather Conditions ◽  
Fire Spread ◽  
New Method ◽  
Ratio Error ◽  
Spread Model ◽  
San Bernardino ◽  
Modeling Errors ◽  
Operational Tool

Fire spread models have a long history, and their use will continue to grow as they evolve from a research tool to an operational tool. This paper describes a new method to analyse two-dimensional fire spread modeling errors, particularly to quantify the uncertainties of fire spread predictions. Measures of error are defined from the respective spread distances of the actual and simulated fires at specified points around their perimeters. A ratio error provides a correction factor for the spread model bias. The characteristics of the error are defined by a probability model, which is used to construct error bounds on fire spread predictions. The method is applied to the Bee Fire, which burned 3848 ha on the San Bernardino National Forest, California, in summer 1996. The study focused on the early, presuppression stages of the fire. A mesoscale spectral model was used to simulate weather conditions on a grid interval of 2 km. The FARSITE system was used to simulate fire growth during the first 105 min of the fire. The case study showed how difficult fire spread modeling is under the conditions presented by the Bee Fire.

Method of License Plate Location Based on Mathematical Morphology and Color Characteristics

2014 ◽  
Vol 602-605 ◽  
pp. 2263-2266
Author(s):  
Ning Lian ◽  
Yan Lei Xu
Keyword(s):  
Mathematical Morphology ◽  
New Method ◽  
License Plate ◽  
License Plate Location ◽  
Color Characteristics ◽  
Image Edge Detection ◽  
Single Method ◽  
Image Edge ◽  
Location Algorithm ◽  
Plate Location

According to restrictions existing in the application of single license plate location algorithm in complicated background. A license plate location algorithm based on mathematical morphology and color characteristics is proposed. Firstly, the new method uses Ostu algorithm to select an optimal threshold, and according to the threshold carries on binary processing, then by using a new method of mathematical morphology for image edge detection. Finally combined mathematical morphology with color characteristic to locate license plate .Experiments show that this new method with higher accuracy and fewer restrictions on background is superior to traditional or a single method and can be widely used.

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