Rafia Mumtaz

Georeferencing of UK DMC stereo-images without ground control points by exploiting geometric distortions

This article describes a new method for the georeferencing of UK-DMC imagery that does not require ground control points (GCPs). The proposed method utilizes satellite ancillary data, and the inter-imager offsets to determine the geolocation of individual pixels. The major step involved is the direct georeferencing of each pixel using satellite GPS and attitude sensor observations. The known separation between the sensors will allow us to determine the geolocations of all pixels that are taken at the same time using the same exterior orientation parameters. Traditional methods for georeferencing use GCPs, which are expensive and time-consuming tasks. Moreover, the traditional method is not suitable for a pushbroom imager because every scan line has a different set of exterior orientation parameters. Therefore, we propose a direct georeferencing approach without GCPs. The major source of error in direct georeferencing is the error in attitude measurements. The reason for this error is considered to be the thermo-elastic effects on the satellite, which affect the sensors’ positioning, causing deformation in the images. These effects have been modelled as a transformation matrix that describes the extent of deformation in the imagery, and is estimated by exploiting the geometric distortions in stereo Earth images. For this purpose, a mathematical model has been developed to demonstrate how inter-image offsets have been introduced into the imagery and affected by thermal deformation. The mathematical model is based on the sensor configuration of UK-DMC satellites. The model has been further inverted to extract the thermal deformation at a given row and column offset. The thermal deformation matrix has been found to mitigate the pointing error up to 1 km. The accuracy of the thermal deformation estimates is highly dependent on the accuracy of image offsets. The accuracy of image offsets is dependent on several factors, which include the image registration method, window size, along-track separation between the sensors, satellite attitude, and resolution of the sensors.

Attitude Determination by Exploiting Geometric Distortions in Stereo Images of DMC Camera

A description is presented of a neoteric approach to determine the orientation of the spacecraft for any arbitrary attitude by exploiting the offsets in the Earth observational imagery from a pair of canted pushbroom sensors. Due to angular separation one of the imager projections is ahead of the other, which causes a delay in the imaging of the same ground features by the sensors. Thus, the angular separation creates perspective and temporal distortions in the imagery, which give rise to inter-image offsets in the overlapping region. A mathematical model is developed using the sensor configuration of the UK-DMC (disaster monitoring constellation) satellite to demonstrate how the offsets are introduced in the imagery and quantify that model with the aid of synthetic images. To determine the attitude from the image offsets, the attitude model is inverted. The accuracy of attitude estimates is highly dependent on the image texture, angular separation between the sensors, spacecraft attitude, and image registration method. With small along-track separation between the sensors, the registration time is very short, thus, changes in the inter-image offsets are not very rapid at small arbitrary rotations. However, with the increase in along-track separation between the sensors, the registration time increases, which allows changes in inter-image offsets to be discerned due to attitude variation and increases the sensitivity of the technique. But with large along-track separation, the attitude estimates are averaged over the registration time period. At small arbitrary rotations with half-a-degree angular separation between the sensors, this technique gives attitude accuracies of ±0.03°. As attitude estimates come directly from the payload rather than a dedicated sensor, this corresponds to significant savings in cost, mass, and volume, which are critical for small satellites.

Image processing and classification in diabetic retinopathy: A review

Diabetic retinopathy is one of the disabling microvascular complications of diabetes mellitus that causes the loss of central vision or in cases complete vision loss if not recognized and cured at the earlier stage. This work reviews the latest techniques in digital image processing and pattern classification employed for the detection of diabetic retinopathy and compares them on the basis of different performance measures like sensitivity, specificity, accuracy and area under the curve in receiver operating characteristic. The classification of diabetic retinopathy follows various steps like pre-processing, feature extraction and classification of microaneurysm, hemorrhages, exudates and cotton woolen spot. In this paper, the reported literature in each domain is analyzed.

Access Control As a Service in Cloud: Challenges, Impact and Strategies

The evolution of service-oriented architecture has given birth to the promising cloud technology, which enables the outsourcing of existing hardware and software information technology (IT) infrastructure via the Internet. Since the cloud offers services to a variety of organizations under the same umbrella, it raises security issues including unauthorized access to resources and misuse of data stored in third-party platform. The fact that the cloud supports multiple tenants is the cause for the biggest concern among organizations: how to prevent malicious users from accessing and manipulating data they have no right to access. In this regard, various access control techniques have been proposed, which concentrate on certain authorization issues like the ease of privilege assignment or the resolution of policy conflicts, while ignoring other important weaknesses such as the lack of interoperability and management issues which arise in the dynamic cloud environment. To cover all these challenges, access control as a service (ACaaS), which stems from its significantly more popular parent, security as a service (SECaaS), is considered a viable solution for mediating cloud service consumers’ access to sensitive data. In this chapter, we assist the cloud community in understanding the various issues associated with providing authorization services in the cloud that may be technical, such as privilege escalation and separation of duties, or managerial, such as the steep requirement of time and money for this purpose. ACaaS is the comprehensive solution to some of the issues highlighted previously. We have also discussed the significance and impact of ACaaS, along with the strategies reported in the literature for providing a secure access to the applications hosted on the cloud. We then holistically cover the authorization requirements of the cloud environment, specifically for software as a service (SaaS) model, evaluating the extant relevant solutions based on certain defined factors from the National Institute of Standards and Technology (NIST)-. The outcome of our research is that an ideal ACaaS should be extensive and holistic, which encompasses all the requisite security and managerial features and provides an efficient and reliable access control mechanism to the cloud consumers that complies with international standards.

Automatic detection of retinal hemorrhages by exploiting image processing techniques for screening retinal diseases in diabetic patients

Diabetic retinopathy (DR) is one of the main retinal abnormalities which is asymptomatic and is the main cause of vision loss in diabetic patients. The computer-aided diagnosis systems based on image processing not only facilitate the doctor but also decrease the diagnosis time. This work represents the automated detection of one of the red lesion, i.e., hemorrhages, which are one of the most distinctive signs of retinal diseases in diabetic patients. In the proposed method, the foremost step is to enhance the image quality by eliminating the background noise and nonuniform illumination. This is achieved by applying the methods such as image contrast enhancement and normalization. The subsequent step is to segment the blood vessels from hemorrhages (using scale-based method) as both of them have the same color. The last step is to delineate the hemorrhages by exploiting the gamma correction and global thresholding techniques. The proposed method has achieved specificity (SP) of 84%, sensitivity (SN) of 87%, and an accuracy of 89 % on the DIARETDB1 database.

Image-based spacecraft pointing model using single-bank dual-band registration

The growing interest in the development of small satellites and the demand for high-resolution imaging has made the pointing and drift rate requirements of a satellite more stringent. To achieve high pointing accuracy, star sensors can be used, but their size and weight are too large for small satellites. The need for keeping the overall cost of the spacecraft down and still achieve adequate pointing accuracies has provoked the development of relatively inexpensive and high-performance attitude systems that can provide competitive pointing accuracies during imaging operations. In order to realize such a system, this research describes a novel approach for finding the attitude of a satellite at any arbitrary rotation by using inter-band offsets from a single multi-spectral imager (MSI). For Earth observational imagery, UK Disaster Monitoring Constellation Earth-pointing MSI is used. This research focuses on the potential use of a narrow angle between the bands of a pushbroom sensor for determining the attitude of a spacecraft. The technique investigated does not require ground control points or knowledge of any ground features, but rather estimates the orientation of the platform through analysis of perspective and timing-based distortions between images. These distortions are assumed translational and affine in nature, with two-dimensional shifts being extracted from imagery using a Singular Value Decomposition-based registration scheme. In order to better understand the effect of attitude on imagery, a model was developed for predicting inter-band shifts given an attitude. This was then used to estimate the shifts between imagery at nominal attitude and given a series of simulated manoeuvres. Several simulations have shown that the row and column offsets represented a straight line. Hence, we expressed the row and column shifts in terms of straight line parameters. These geometric attributes are then represented in terms of Euler axis/angle to find the mapping for the elements of the general rotation matrix. Once the mapping is computed for the elements of the rotation matrix, we used the standard equations to determine the angle of rotation and Euler axis. The accuracy of attitude estimates depends on the magnitude of angular separation between the cameras, orientation of spacecraft, sensor resolution, image texture, and image registration method. The technique proposed in this study may however be applied to any satellite with pushbroom sensors that have a discernable along track separation and sufficient overlap.

Accuracy assessment of geo-locations using multiresolution interpolated DEMs

This paper provides novel analysis of existing interpolation techniques and suggests improvement for more accurate orthorectification of satellite imagery. Traditional methods for measuring geo-location use Ground Control Points (GCPs). The accuracy of these methods depends on the accuracy of GCPs. The accuracy of geolocations can also be improved by using Digital Elevation Model (DEM) which incorporates topographic relief displacement to measure geographic locations. Since the accuracy of geographic locations is dependent on the resolution of DEM, in our study, the accuracy of geo-locations was assessed using interpolated DEMs of multiple resolutions. The comparative analysis showed that the accuracy of geo-locations can be improved by increasing the resolution of DEM using interpolation.