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http://localhost:8081/xmlui/handle/123456789/9
2023-12-31T13:31:51ZANALYSES OF DESPECKLING ALGORITHMS FOR POLARIMETRIC SAR DATA
http://localhost:8081/xmlui/handle/123456789/15544
Title: ANALYSES OF DESPECKLING ALGORITHMS FOR POLARIMETRIC SAR DATA
Authors: Sharma, Rakesh
Abstract: Polarimetric SAR (PolSAR) systems can characterize different land features based
on decomposition parameters. The estimation of these parameters is often biased
due to the presence of speckle noise. Speckle noise in PolSAR returns depicts a
peculiar signal-dependent phenomenon and is better characterized by a multiplicative
model rather than an additive one. Also, as the noise statistics are far from Gaussian,
specialized tools for PolSAR speckle filtering different from the standard image
denoising tools are required. PolSAR data is necessarily characterized by the polarimetric/
scattering information and its spatial resolution. So, in the process of speckle
filtering, these features of the PolSAR data should be significantly preserved. Indeed,
this is the main motivation behind the work carried out in this thesis. Accordingly,
this thesis is divided into two main areas of the study. The first part concerns
about development and analyses of speckle filters for full-pol SAR data. And the
second part deals with the development and analysis of speckle filter for hybrid-pol
SAR data. In this process, four novel PolSAR speckle filters are developed and presented
that apart from reducing noise, preserve the polarimetric information as well
as the spatial resolution of the data. First, the l1-NLM filter that performs better than
conventional non-local patch-based PolSAR filter in excessive noise is presented. l1-
NLM filter is implemented by the famousWeiszfeld’s algorithm to find the weighted
l1-norm distance minimization estimate. Second, the CFAR-PolSAR filter that integrates
Wishart based pre-classification to PolSAR speckle filtering is demonstrated.
CFAR-PolSAR filter achieves extended noise reduction and edge preservation with
lesser computations. Third, a texture classification based filter (TCBF) is presented
that exploits the differences between texture variations and speckle heterogeneity
in the PolSAR data. The speckle noise generates a heterogeneity pattern in PolSAR
data that is distinct from textural variations due to heterogeneous media. Also, the
K-distribution similarity of covariance matrices is derived. Fourth, a speckle filtering
approach named as Stokes based sigma filter (SBSF) based on probability density
function of Stokes parameters is presented. Also, a new sigma range calculation algorithm
depending on degree of polarization and mean intensities is presented.
In order to illustrate the relevance of above PolSAR speckle filters, the experiix
Abstract
ments are conducted over variety of PolSAR datasets. In this work, two full-pol
single-look RADARSAT-2 datasets acquired over Mumbai (India) coastal area and
San Fransisco (USA) bay area are used. A four-look full-pol AIRSAR dataset acquired
over San Fransisco (USA) bay area is also used. Analysis of the efficacy of SBSF on
real hybrid-pol SAR data is demonstrated on single-look hybrid-pol RISAT-1 data acquired
over Mumbai city (India). Apart from these real PolSAR datasets, simulated
datasets are generated through Monte Carlo simulation approach and analyzed for
evaluation of the filtering performance.
In summary, this thesis contributes in the development of PolSAR speckle filters
that: 1) preserve scattering information, textural information, and data statistics,
2) enhance averaging in homogeneous regions, 3) filter heterogeneous regions with
preservation of sharp details and edges, 4) un-filter strong targets, and 5) reduce
computational complexity.2019-10-01T00:00:00ZINTERFACIAL CHARGE TRANSFER PROCESSES IN QUANTUM DOT SOLAR CELLS
http://localhost:8081/xmlui/handle/123456789/15542
Title: INTERFACIAL CHARGE TRANSFER PROCESSES IN QUANTUM DOT SOLAR CELLS
Authors: Verma, Upendra Kumar
Abstract: Quantum dots (QDs) are extensively used in photovoltaic devices due to their unique
properties: bandgap tunability, capability of multiple exciton generation, up/down wavelength
conversion. The improvement in device performance is attributed to the enhancement in optical
absorption, quantum efficiency, and reduction in thermalization losses. Good optical, as well as
electrical properties of the QDs, are essential for efficient device operation. Charge transport
and carrier recombination in the QDs are the key processes that affect the device performance
and these processes can be easily tuned during the synthesis of QDs and fabrication of the
device.
In this work, current-voltage characteristics in bilayer heterojunction diodes are studied
(effects of energy barriers, layer thicknesses, etc.) and separated into three working regimes
based on the energy band diagram of the device. Subsequently, a model for multilayer quantum
dot organic solar cells has been developed that explores the impact of electronic processes
(carrier recombination, tunneling, injection, etc.) in QDs on the current-voltage (J-V)
characteristic of the solar cells. Solar cell characteristics can be controlled by the quantum dot
layers. The bimolecular recombination coefficient of QDs is a prime factor that controls the
open-circuit voltage without any significant reduction in short circuit current. To verify our
proposed model, various core-shell QDs have been fabricated and its interlayer is inserted
between the donor and acceptor layer in the device. The addition of QDs has improved the
optical absorption in the device resulting in an increase in photo-current/short circuit current
density and open-circuit voltage of the solar cell but the current-voltage characteristics show an
s-shaped curve in the fourth quadrant which results in drastically reduced fill factor. The reason
behind the appearance of s-kink in experimentally obtained J-V characteristic of QD solar cells
has been analyzed with the model. According to the model, the capture/emission time and
tunneling rate coefficient in QDs are individually responsible for degradation in device
performance via an undesirable s-shaped J-V characteristic of hybrid organic/inorganic
quantum dot solar cells. Thus, injection/extraction rate, tunneling among QDs and
recombination in QDs are essential factors that are required to be optimized for efficient QD
solar cells. The structural and energetic disorders at various interfaces, surface properties of
QDs, fabrication process, etc. must be taken into consideration to achieve an efficient device.2019-07-01T00:00:00ZSPINTRONICS BASED QUANTUM COMPUTING ARCHITECTURES
http://localhost:8081/xmlui/handle/123456789/15541
Title: SPINTRONICS BASED QUANTUM COMPUTING ARCHITECTURES
Authors: Aravind, Kulkarni Anant
Abstract: A quantum computer performs computations on the principles of quantum mechanics that enables faster speed and higher security than classical computers, and also has the ability to process large amount of information due to its inherent ability of parallel processing. The important building blocks of the quantum computer are qubit, quantum register, quantum logic, quantum network, quantum reversibility, quantum teleportation, quantum data compression, quantum cryptography, universal quantum computing, and quantum algorithm. Quantum computers rely on basic quantum principles of superposition and entanglement. The time evolution of an arbitrary quantum state is computationally more powerful than evolution of a digital logic state. Theoretical quantum computing based on the rotation of the qubits has proved that there is a possibility of quantum devices to address the complex computing problems. However, presently, there is no computer in existence that can completely work on the principles of quantum mechanics. Therefore, the enormous advantages of quantum computing in comparison to its classical counterpart have forced researchers to explore the possibilities of physical realization with the help of emerging technologies. The basic requirements of Divincenzo criteria have to be fulfilled for the successful implementation of the quantum computing. This criteria suggest that the system realizing the quantum computing should have well characterized qubit; proper initial state of all qubits; enough isolation to the qubit(s); precise qubit state manipulation and facilitation of qubits interaction should be in time less than the qubit decoherence time; and the physical system should facilitate the measurement of each qubit to obtain the output of the quantum computation. Spintronics is one of the most efficient ways to physically realize quantum computing due to strong analogy of electron spin to the qubit. Spin-torque based on-chip qubit architecture paves the way for the research in spintronics based physical realization of quantum computer. However, the qubit decoherence is a critical issue in spin qubit architecture from the complex computing point of view. This issue can be dealt by two ways in this thesis; firstly, by utilizing the materials with spin qubits having very high spin coherence, and secondly, by reducing and optimizing the number of elementary quantum operations with the help of elementary quantum gate
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library. This thesis presents both ways in detail with demonstrations of reduction in number of elementary operations by elementary quantum gate library. A computing platform is realized using reduced elementary gates such as CNOT, SWAP, Toffoli, and Fredkin wherein the reduction in number of elementary operations is 36.36%, 36.36%, 35.44%, 35.64%, respectively. The optimization of the reduced number of operations for the quantum circuits representing the Boolean logics AND, OR, XOR, Hall Adder (HA), and Full Adder (FA), is also achieved with a reduction after optimization of 37.97%, 41.58%, 45.45%, 40%, and 40.55%, respectively. A quantum Fourier transform that is an integral part of the Shor's algorithm for the number factorization is also reduced and optimized. The reduction of 35.71% in number of elementary operations for the quantum Fourier transform is also demonstrated. Various other complex computing operations can be realized using the spin torque based qubit architecture. This thesis lays strong foundation for researchers aspiring to work in the area of quantum computing using spintronics platform and also discusses the associated challenges.2019-08-01T00:00:00ZTARGET LOCALIZATION WITH VIDEO STABILIZATION USING VISUAL FEATURE TRACKING
http://localhost:8081/xmlui/handle/123456789/15540
Title: TARGET LOCALIZATION WITH VIDEO STABILIZATION USING VISUAL FEATURE TRACKING
Authors: Verma, Kamlesh
Abstract: Visual surveillance is one very important requirement for present and future computer
vision technologies. Video may be recorded using a digital camera which may be handheld
or mounted on some moving platform of a vehicle. Consequently, the recorded video
is generally unstabilized on account of unwanted and unintentional jerks and motion of
the camera. This unwanted motion may be due to shaking of hand, vehicle running on
irregular terrain or due to vehicle engine vibrations. Such unstabilized and shaky videos
are of poor quality, noisy, motion blurred and neither suitable for viewing nor for post
processing like target detection and tracking. Target detection and tracking is one prime
research problem in computer vision area due to its increasing demand in many visual applications
ranging from dynamic motion based detection, face detection, threat detection,
automatic visual surveillance, indexing of video, crowd management, behavioral analysis,
automatic vehicle drive, military search and track of potential threats for integrated
fire control solutions. This problem of target tracking poses challenge due to scene illumination
variations, non-rigid target body, frequent pose variation of target, occlusion,
information loss due to conversion of scene from 3D to 2D, image noise, complex target
motion, different shapes of target and so on.
In order to enable the use of unstabilized and shaky videos for surveillance and other
purposes, this thesis addresses two major issues: (1) Video stabilization, and (2) localization
of targets of interests in the video scene.
Video stabilization is a necessary requirement for creating stable video footage that
can be used reliably for visual communication, smooth high quality visuals and for any
post processing of video. There are three types of video stabilization techniques available
in the literature, namely, electronic image stabilization (uses sensors and actuators hardware),
optical image stabilization (uses moving optical components) and digital image
stabilization (uses image processing techniques for detection and compensation of global
frame motion vector). In this thesis, we propose to use feature tracking based image/video
processing technique to meet this requirement. Feature tracking is used to estimate the
frame-to-frame motion in the video. The unwanted motion is then estimated and removed
from the video to display the video footage as if the unwanted motion had not occurred.
The resulting stabilized video enables the user to easily detect, track and locate targets in
the video scene.
Target localization involves estimating the world position of an identified target while
visual tracking may be defined as estimating the frame-to-frame trajectory of the object
of interest in a video scene. There are two main components in visual tracking, viz. detection
of target (by extracting target features) and tracking of target (by estimating local
motion vector of target). Visual tracking has always been a challenging research problem
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among the researchers in the field of computer vision. Development of algorithm for visual
tracking involves target representation (point, geometrical shapes, silhouette, articulated,
contour or skeletal model), target appearance (probability density, templates, active
or multi-view appearance models), selection of features for visual tracking (color, edge,
optical flow or texture), target detection (point detector, subtraction of background, segmentation,
mean-shift clustering, graph cut method, active contours, supervised learning
(adaptive boosting, support vector machines) and finally visual tracking (point, kernel or
silhouette). In this thesis, several different visual features, such as Gabor wavelet features,
Speeded Up Robust Feature (SURF), etc. are used for precise detection and localization
of targets while Kalman filtering for tracking these targets.
Real time operation of visual object trackers is indispensable for almost all of its
applications. Since object detection and tracking algorithms are generally computationintensive,
this thesis also proposes hardware realization of the proposed techniques for
video stabilization and target localization. Further, option for incorporating hot swappable
redundancy in the system is also considered in this thesis so as to improve the reliability
of the system.
This thesis begins with an introduction to the problem of video stabilization and target
localization in Chapter 1 followed by a discussion on the state-of-the-art in the development
of respective technology in video stabilization and target localization in Chapter 2.
Our proposed methods for digital video stabilization are presented in Chapter 3. Chapter
4 discusses our proposed target detection and tracking algorithms. Methods for target
localization in unstabilized videos, with simultaneous video stabilization are developed
in Chapter 5. Hardware implementation of the above proposed methods for video stabilization
and target localization is proposed in Chapter 6. The conclusions drawn from this
work and a discussion on possible future work are finally presented in Chapter 7.
In summary, this thesis contributes in the development of algorithms for digital video
stabilization and target localization. Hardware development for electronics image stabilization
is also proposed. The thesis is well supported with promising results and comparative
analysis with benchmarked algorithms proving the effectiveness of the algorithms.2020-03-01T00:00:00Z