Reham Gharbia

Fusion of multi-spectral and panchromatic satellite images using principal component analysis and fuzzy logic

ABSTRACT In this paper, we propose a fuzzy-based multi-spectral (MS) and panchromatic (PAN) image... more ABSTRACT In this paper, we propose a fuzzy-based multi-spectral (MS) and panchromatic (PAN) image fusion approach which provides a tradeoff solution between spectral and spatial fidelity and is able to preserve more detail in terms of spectral and spatial information. First, we perform principal component analysis on the multi-spectral images and utilise the first principal component to extract matched low and high frequency coefficients. We then apply fuzzy-based image fusion rules to fuse the first principal component with the PAN image, followed by fusing the approximation coefficients. The proposed approach is tested on several satellite images and shown to provide a feasible and effective approach.

Deep Learning for Automatic Extraction of Water Bodies Using Satellite Imagery

Journal of The Indian Society of Remote Sensing, Jun 11, 2023

The study introduces an automated approach for extracting water bodies from satellite images usin... more The study introduces an automated approach for extracting water bodies from satellite images using the Faster R-CNN algorithm. The approach was tested on two datasets consisting of water body images collected from Sentinel-2 and Landsat-8 (OLI) satellite images, totaling over 3500 images. The results showed that the proposed approach achieved an accuracy of 98.7% and 96.1% for the two datasets, respectively. This is significantly higher than the accuracy achieved by the convolutional neural network (CNN) approach, which achieved 96% and 80% for the two datasets, respectively. These findings highlight the effectiveness of the proposed approach in accurately mapping water bodies from satellite imagery. Additionally, the Sentinel-2 dataset performed better than the Landsat dataset in both the Faster R-CNN and CNN approaches for water body extraction.

Download

Region-based Image Fusion Approach of Panchromatic and Multi-spectral Images

Springer eBooks, 2015

In this paper, a region-based image fusion approach were proposed based on the stationary wavelet... more In this paper, a region-based image fusion approach were proposed based on the stationary wavelet transform (SWT) in conjunction with marker-controlled watershed segmentation technique. The SWT is redundant, linear and shift invariant and these properties allow SWT to be realized exploiting a recursive algorithm and gives a better approximation than the DWT. The performance of the fusion approach is illustrated via experimental results obtained with a broad series of images and the experimental results used the MODIS multi-spectral bands and Spot panchromatic band to validate the proposed image fusion technique. Moreover, the visual presentation and different evaluation criteria including the standard deviation, the entropy information, the correlation coefficient, the root mean square error, the peak signal to noise ratio and the structural similarity index was used to evaluate the obtained results. The proposed approach achieves superior results compared with the existing work.

Land Cover Classification Using Deep Convolutional Neural Networks

Advances in intelligent systems and computing, 2021

Carbon Monoxide Air Pollution Monitoring Approach in Africa During COVID-19 Pandemic

Studies in systems, decision and control, 2021

In December of 2019, a new coronavirus, called SARS-CoV-2, began in Wuhan, China, known as COVID-... more In December of 2019, a new coronavirus, called SARS-CoV-2, began in Wuhan, China, known as COVID-19. The COVID-19 epidemic has expanded dramatically. The epidemic lockdown of COVID-19 affected air quality due to severe changes in human behavior. Recent research shows that air quality has improved during the COVID-19 pandemic due to social lockdown measures. Africa can avoid outbreaks of respiratory diseases, including COVID-19, with cleaner air. However, monitoring air pollution over the continent has required complex efforts to track air quality due to policies, borders, and the continent’s nature. Now, satellite data can monitor air quality in cities and countries and bridge the gap in African countries without ground sensors. This paper examines the impact of lockdown on COVID-19 on air pollution in Africa. This study included measurements of the total column concentration of carbon monoxide (CO) from the tropospheric monitoring instrument (TROPOMI) on the Sentinel-5 precursor satellite. This study analyzed the global carbon dioxide concentration in Africa before, during, and after the COVID-19 pandemic from 15 March to 6 June 2019 and 2020. The results here indicate a small decrease in the CO levels because more than nine hundred million people in Africa depend on energy sources polluted for household uses, resulting from wood-burning, kerosene, and charcoal. Many millions of people in Africa live in small crowded houses, bad ventilation and building materials. These dangers cause rising air pollution.

Image Fusion Techniques in Remote Sensing

arXiv (Cornell University), Mar 11, 2014

Remote sensing image fusion is an effective way to use a large volume of data from multisensor im... more Remote sensing image fusion is an effective way to use a large volume of data from multisensor images. Most earth satellites such as SPOT, Landsat 7, IKONOS and QuickBird provide both panchromatic (Pan) images at a higher spatial resolution and multispectral (MS) images at a lower spatial resolution and many remote sensing applications require both high spatial and high spectral resolutions, especially for GIS based applications. An effective image fusion technique can produce such remotely sensed images. Image fusion is the combination of two or more different images to form a new image by using a certain algorithm to obtain more and better information about an object or a study area than. The image fusion is performed at three different processing levels which are pixel level, feature level and decision level according to the stage at which the fusion takes place. There are many image fusion methods that can be used to produce high resolution multispectral images from a high resolution pan image and low resolution multispectral images. This paper explores the major remote sensing data fusion techniques at pixel level and reviews the concept, principals, limitations and advantages for each technique. This paper focused on traditional techniques like intensity hue-saturation-(HIS), Brovey, principal component analysis (PCA) and Wavelet.

Download

Swarm Intelligence Based on Remote Sensing Image Fusion

Advances in computational intelligence and robotics book series, 2017

This chapter presents a remote sensing image fusion based on swarm intelligence. Image fusion is ... more This chapter presents a remote sensing image fusion based on swarm intelligence. Image fusion is combining multi-sensor images in a single image that has most informative. Remote sensing image fusion is an effective way to extract a large volume of data from multisource images. However, traditional image fusion approaches cannot meet the requirements of applications because they can lose spatial information or distort spectral characteristics. The core of the image fusion is image fusion rules. The main challenge is getting suitable weight of fusion rule. This chapter proposes swarm intelligence to optimize the image fusion rule. Swarm intelligence algorithms are a family of global optimizers inspired by swarm phenomena in nature and have shown better performance. In this chapter, two remote sensing image fusion based on swarm intelligence algorithms, Particle Swarm Optimization (PSO) and flower pollination algorithm are presented to get an adaptive image fusion rule and comparative between them.

Download

Remote Sensing Image Registration Based on Particle Swarm Optimization and Mutual Information

Springer eBooks, 2015

ABSTRACT The image registration is an indispensable process in remote sensing image processing. T... more ABSTRACT The image registration is an indispensable process in remote sensing image processing. The remote sensing registration data is the process of aligning one image to a second image of the same scene that is acquired at the same or at different times by the different or the same sensors. This paper proposes an optimization approach for remote sensing image registration. The approach is proposed for determining pairs of corresponding points between the images, the approach based on the implementation of particle swarm optimization (PSO) used as a function optimizer and mutual information (MI) is used as a similarity measure. The first, Landmarks were chosen manually and used thin plate spline (TPS) to provide a geometric representation for the relative locations of corresponding landmarks. Secondly, MI was used as a cost function to determine the degree of similarity between two images. Finally, PSO was used to improve the correspondence between the landmarks and to maximize MI function.

Deep Learning for Automatic Extraction of Water Bodies Using Satellite Imagery

Journal of the Indian Society of Remote Sensing

The study introduces an automated approach for extracting water bodies from satellite images usin... more The study introduces an automated approach for extracting water bodies from satellite images using the Faster R-CNN algorithm. The approach was tested on two datasets consisting of water body images collected from Sentinel-2 and Landsat-8 (OLI) satellite images, totaling over 3500 images. The results showed that the proposed approach achieved an accuracy of 98.7% and 96.1% for the two datasets, respectively. This is significantly higher than the accuracy achieved by the convolutional neural network (CNN) approach, which achieved 96% and 80% for the two datasets, respectively. These findings highlight the effectiveness of the proposed approach in accurately mapping water bodies from satellite imagery. Additionally, the Sentinel-2 dataset performed better than the Landsat dataset in both the Faster R-CNN and CNN approaches for water body extraction.

Download

A Novel Whale Based Optoelectronics System for Securing Healthcare Data in Internet of Things (IoT)-Based Cloud Environment

Journal of Nanoelectronics and Optoelectronics

Healthcare data, encompassing vital signs such as temperature, heart rate, respiratory rate, and ... more Healthcare data, encompassing vital signs such as temperature, heart rate, respiratory rate, and blood pressure along with results from the lab and needs to be kept secure and private as it is used to monitor the health of patients in real-time and make decisions on their healthcare. Unfortunately, healthcare data in IoT-based cloud systems are at risk of malicious attacks, including access control bypass, malware injection, and data privacy violations; this is due to the distributed nature of cloud computing, which requires the processing and storage of sensitive information among multiple servers, heightening the risk of data breaches. The current security algorithms are unable to understand the complexity of healthcare data for effective security; thus, robust security measures based on the inherent data features must be employed to strengthen encryption, access control, and two-factor authentication for guaranteeing the security of healthcare data in a cloud-powered IoT environm...

Image Fusion Techniques in Remote Sensing

Remote sensing image fusion is an effective way to use a large volume of data from multisensor im... more Remote sensing image fusion is an effective way to use a large volume of data from multisensor images. Most earth satellites such as SPOT, Landsat 7, IKONOS and QuickBird provide both panchromatic (Pan) images at a higher spatial resolution and multispectral (MS) images at a lower spatial resolution and many remote sensing applications require both high spatial and high spectral resolutions, especially for GIS based applications. An effective image fusion technique can produce such remotely sensed images. Image fusion is the combination of two or more different images to form a new image by using a certain algorithm to obtain more and better information about an object or a study area than. The image fusion is performed at three different processing levels which are pixel level, feature level and decision level according to the stage at which the fusion takes place. There are many image fusion methods that can be used to produce high resolution multispectral images from a high resol...

Download

Swarm Intelligence Based on Remote Sensing Image Fusion: Comparison Between the Particle Swarm Optimization and the Flower Pollination Algorithm

This chapter presents a remote sensing image fusion based on swarm intelligence. Image fusion is ... more This chapter presents a remote sensing image fusion based on swarm intelligence. Image fusion is combining multi-sensor images in a single image that has most informative. Remote sensing image fusion is an effective way to extract a large volume of data from multisource images. However, traditional image fusion approaches cannot meet the requirements of applications because they can lose spatial information or distort spectral characteristics. The core of the image fusion is image fusion rules. The main challenge is getting suitable weight of fusion rule. This chapter proposes swarm intelligence to optimize the image fusion rule. Swarm intelligence algorithms are a family of global optimizers inspired by swarm phenomena in nature and have shown better performance. In this chapter, two remote sensing image fusion based on swarm intelligence algorithms, Particle Swarm Optimization (PSO) and flower pollination algorithm are presented to get an adaptive image fusion rule and comparative...

Download

Carbon Monoxide Air Pollution Monitoring Approach in Africa During COVID-19 Pandemic

The Global Environmental Effects During and Beyond COVID-19, 2021

In December of 2019, a new coronavirus, called SARS-CoV-2, began in Wuhan, China, known as COVID-... more In December of 2019, a new coronavirus, called SARS-CoV-2, began in Wuhan, China, known as COVID-19. The COVID-19 epidemic has expanded dramatically. The epidemic lockdown of COVID-19 affected air quality due to severe changes in human behavior. Recent research shows that air quality has improved during the COVID-19 pandemic due to social lockdown measures. Africa can avoid outbreaks of respiratory diseases, including COVID-19, with cleaner air. However, monitoring air pollution over the continent has required complex efforts to track air quality due to policies, borders, and the continent’s nature. Now, satellite data can monitor air quality in cities and countries and bridge the gap in African countries without ground sensors. This paper examines the impact of lockdown on COVID-19 on air pollution in Africa. This study included measurements of the total column concentration of carbon monoxide (CO) from the tropospheric monitoring instrument (TROPOMI) on the Sentinel-5 precursor satellite. This study analyzed the global carbon dioxide concentration in Africa before, during, and after the COVID-19 pandemic from 15 March to 6 June 2019 and 2020. The results here indicate a small decrease in the CO levels because more than nine hundred million people in Africa depend on energy sources polluted for household uses, resulting from wood-burning, kerosene, and charcoal. Many millions of people in Africa live in small crowded houses, bad ventilation and building materials. These dangers cause rising air pollution.

Multi-spectral and panchromatic image fusion approach using stationary wavelet transform and swarm flower pollination optimization for remote sensing applications

Future Generation Computer Systems, 2018

Abstract This paper proposes a multi-spectral (MS) and panchromatic (Pan) image fusion approach b... more Abstract This paper proposes a multi-spectral (MS) and panchromatic (Pan) image fusion approach based on the flower pollination algorithm optimization (FPA). The FPA is used to get an optimal fused image. The image fusion quality depends on the choice of the weight of fusion rule. The proposed approach uses FPA to optimize the weights of a fusion rule to make a perfect image fusion process. FPA is a nature-inspired algorithm, based on the characteristics of a flower pollination process. FPA averts trapping in local optimal solution. In this paper, the remote sensing image fusion based on flower pollination algorithm is compared to several states of the art image fusion approaches including Intensity-hue-saturation (IHS) image fusion; stationary wavelets transform image fusion based on the average weight fusion rule (SWT-AW) and the image fusion based on the particle swarm optimization (PSO). The experimental results used MODIS satellite series with spatial resolutions 250 m, 500 m, and 1 km, which are low spatial resolution and multispectral images; and Pan image of SPOT satellite is high spatial resolution 10 m to produce synthetic imagery at SPOT spatial resolutions and MODIS multispectral resolution at the same time. The experimental results prove that the proposed remote sensing image fusion approach can illustrate a better performance than the other approaches. The experimental results show that the approach offers up to 20% enhancement in Peak Signal to Noise Ratio (PSNR), 1% enhancement in Structural Similarity Index (SSIM), 1% and 0.5% enhancement in entropy information (EI) than best existing particle swarm optimization (PSO) approach. The results indicate that the proposed approach outperforms over existing approaches.

An adaptive image fusion rule for remote sensing images based on the particle swarm optimization

2016 International Conference on Computing, Communication and Automation (ICCCA), 2016

This paper proposes an adaptive remote sensing image fusion technique based on the particle swarm... more This paper proposes an adaptive remote sensing image fusion technique based on the particle swarm optimization (PSO) to get the optimum fused image. Firstly, the principal component analysis (PCA) is applied such as feature extraction. The PCA is applied to the multi-spectral (MS) images to concentrate the spatial resolution. Secondly, the discrete cosine transform (DCT) transforms the images into the frequency domain. Thirdly, the particle swarm optimization (PSO) is used to obtain an adaptive weight of the fusion rule. Then, the adaptive fusion rule is applied to the DCT coefficients. Finally, the fused image is obtained through the inverse of principal component analysis (IPCA) and the inverse of the discrete cosine transform (IDCT). The different satellite sensors have different characteristics in reflecting spectral and spatial information of the same scene. Therefore, the proposed technique was implemented on many satellite images such as MODIS, ETM+, SPOT, ASTER and MSS satellite. The experimental results demonstrated that the adaptive remote sensing image fusion technique based on the PSO preserves the spectral resolution and improves the spatial information.

Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014. Springer International Publishing, 2014

Image Fusion Techniques in Remote Sensing

Remote sensing image fusion is an effective way to use a large volume of data from multisensor im... more Remote sensing image fusion is an effective way to use a large volume of data from multisensor images. Most earth satellites such as SPOT, Landsat 7, IKONOS and QuickBird provide both panchromatic (Pan) images at a higher spatial resolution and multispectral (MS) images at a lower spatial resolution and many remote sensing applications require both high spatial and high spectral resolutions, especially for GIS based applications. An effective image fusion technique can produce such remotely sensed images. Image fusion is the combination of two or more different images to form a new image by using a certain algorithm to obtain more and better information about an object or a study area than. The image fusion is performed at three different processing levels which are pixel level, feature level and decision level according to the stage at which the fusion takes place. There are many image fusion methods that can be used to produce high resolution multispectral images from a high resolution pan image and low resolution multispectral images. This paper explores the major remote sensing data fusion techniques at pixel level and reviews the concept, principals, limitations and advantages for each technique. This paper focused on traditional techniques like intensity hue-saturation-(HIS), Brovey, principal component analysis (PCA) and Wavelet.

Download

Remote Sensing Image Fusion Approach Based on Brovey and Wavelets Transforms

Advances in Intelligent Systems and Computing, 2014

Remote Sensing Image Registration Based on Particle Swarm Optimization and Mutual Information

Advances in Intelligent Systems and Computing, 2015

The image registration is an indispensable process in remote sensing image processing. The remote... more The image registration is an indispensable process in remote sensing image processing. The remote sensing registration data is the process of aligning one image to a second image of the same scene that is acquired at the same or at different times by the different or the same sensors. This paper proposes an optimization approach for remote sensing image registration. The approach is proposed for determining pairs of corresponding points between the images, the approach based on the implementation of particle swarm optimization (PSO) used as a function optimizer and mutual information (MI) is used as a similarity measure. The first, Landmarks were chosen manually and used thin plate spline (TPS) to provide a geometric representation for the relative locations of corresponding landmarks. Secondly, MI was used as a cost function to determine the degree of similarity between two images. Finally, PSO was used to improve the correspondence between the landmarks and to maximize MI function.

Download

Land Cover Classification Using Deep Convolutional Neural Networks

Uploads

Papers by Reham Gharbia

Log In