Persistent scatterer aided facade lattice extraction in single airborne optical oblique images

We present a new method to extract patterns of regular facade structures from single optical oblique images. To overcome the missing three-dimensional information we incorporate structural information derived from Persistent Scatter (PS) point cloud data into our method. Single oblique images and PS point clouds have never been combined before and offer promising insights into the compatibility of remotely sensed data of different kinds. Even though the appearance of facades is significantly different, many characteristics of the prominent patterns can be seen in both types of data and can be transferred across the sensor domains. To justify the extraction based on regular facade patterns we show that regular facades appear rather often in typical airborne oblique imagery of urban scenes. The extraction of regular patterns is based on well established tools like cross correlation and is extended by incorporating a module for estimating a window lattice model using a genetic algorithm. Among others the results of our approach can be used to derive a deeper understanding of the emergence of Persistent Scatterers and their fusion with optical imagery. To demonstrate the applicability of the approach we present a concept for data fusion aiming at facade lattices extraction in PS and optical data

Ultrasound-modulated optical tomography with intense acoustic bursts

Ultrasound-modulated optical tomography (UOT) detects ultrasonically modulated light to spatially localize multiply scattered photons in turbid media with the ultimate goal of imaging the optical properties in living subjects. A principal challenge of the technique is weak modulated signal strength. We discuss ways to push the limits of signal enhancement with intense acoustic bursts while conforming to optical and ultrasonic safety standards. A CCD-based speckle-contrast detection scheme is used to detect acoustically modulated light by measuring changes in speckle statistics between ultrasound-on and ultrasound-off states. The CCD image capture is synchronized with the ultrasound burst pulse sequence. Transient acoustic radiation force, a consequence of bursts, is seen to produce slight signal enhancement over pure ultrasonic-modulation mechanisms for bursts and CCD exposure times of the order of milliseconds. However, acoustic radiation-force-induced shear waves are launched away from the acoustic sample volume, which degrade UOT spatial resolution. By time gating the CCD camera to capture modulated light before radiation force has an opportunity to accumulate significant tissue displacement, we reduce the effects of shear-wave image degradation, while enabling very high signal-to-noise ratios. Additionally, we maintain high-resolution images representative of optical and not mechanical contrast. Signal-to-noise levels are sufficiently high so as to enable acquisition of 2D images of phantoms with one acoustic burst per pixel

New methods for deep tissue imaging

Microscopes play vital role biological science and medicine. For single photon microscopies, the scattering of photons makes regions of interest located a few hundred microns beneath the surface inaccessible. Multi-photon microscopes are widely used for minimally invasive in vivo brain imaging due to their increased imaging depth. However, multi-photon microscopes are hampered by limited dynamic range, preventing weak sample features from being detected in the presence of strong features, or preventing the capture of unpredictable bursts in sample strength. In the first part of the thesis, I present a solution to vastly improve the dynamic range of a multi-photon microscope while limiting potential photodamage. Benefits are shown in both structural and in-vivo functional mouse brain imaging applications. In the second section of the thesis work, I explore a completely different approach towards deep tissue imaging by changing the type of radiation from light to ultrasound. Inspired by an optical phase contrast technique invented in the lab, I developed an unprecedented ultrasound imaging system that can visualize the ultrasound phase contrast in the sample. The ultrasound phase contrast technique is able to visualize local sound speed variations instead of local reflectivity. Compared with existing sound speed tomography systems, our technique eliminates the cumbersome sound speed reconstruction process. The research work in this section contains three parts. In the first part, we designed a low-cost single element scanning system as proof of concept. In the second part, we implemented the ultrasound phase contrast imaging system on a commercial linear phased transducer array and an imaging apparatus designed for samples with finite thickness. In the third part, we studied the feasibility of ultrasound phase contrast imaging in arbitrarily thick tissue. We presented a complete workflow of theoretical study, simulation, prototyping and experimental testing for all three parts.2020-02-28T00:00:00

NON-INVASIVE OPTICAL DETECTION OF EPITHELIAL CANCER USING OBLIQUE INCIDENCE DIFFUSE REFLECTANCE SPECTROSCOPY

This dissertation describes the design, fabrication and testing of an oblique incidence diffuse reflectance spectrometry (OIDRS) system for in-vivo and noninvasive detection of epithelial cancer. Two probes were fabricated using micromachining technology, which plays a significant role in the probe development by enabling device miniaturization, low-cost fabrication and precise assembly. The fist probe was developed and clinically tested for skin cancer detection. This probe consists of three source fibers, two linear array of collection fibers and four micromachined positioning devices for accurate alignment of the fibers. The spatially resolved diffuse reflectance spectra from 167 pigmented and 78 non-pigmented skin abnormalities were measured and used to design a set of classifiers to separate them into benign or malignant ones. These classifiers perform with an overall classification rate of 91%. The absorption and reduced scattering coefficient spectra were estimated to link the anatomic and physiologic properties of the lesions with the optical diagnosis. The melanoma cases presented larger average absorption and reduced scattering spectra than the dysplastic and benign ones. A second probe was designed to demonstrate the feasibility of a miniaturized ?side viewing? optical sensor probe for OIDRS. The sensor probe consists of a lithographically patterned polymer waveguides chip and two micromachined positioning substrates. This miniaturize probe was used to measure twenty ex-vivo esophageal samples. Two statistical classifiers were designed to separate the esophageal cases. The first one distinguishes benign and low dysplastic from high dysplastic and cancerous lesions. The second classifier separates benign lesions from low dysplastic ones. Both classifiers generated a classification rate of 100%

Elevation and Deformation Extraction from TomoSAR

3D SAR tomography (TomoSAR) and 4D SAR differential tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to provide an essential innovation of SAR Interferometry for many applications, sensing complex scenes with multiple scatterers mapped into the same SAR pixel cell. However, these are still influenced by DEM uncertainty, temporal decorrelation, orbital, tropospheric and ionospheric phase distortion and height blurring. In this thesis, these techniques are explored. As part of this exploration, the systematic procedures for DEM generation, DEM quality assessment, DEM quality improvement and DEM applications are first studied. Besides, this thesis focuses on the whole cycle of systematic methods for 3D & 4D TomoSAR imaging for height and deformation retrieval, from the problem formation phase, through the development of methods to testing on real SAR data. After DEM generation introduction from spaceborne bistatic InSAR (TanDEM-X) and airborne photogrammetry (Bluesky), a new DEM co-registration method with line feature validation (river network line, ridgeline, valley line, crater boundary feature and so on) is developed and demonstrated to assist the study of a wide area DEM data quality. This DEM co-registration method aligns two DEMs irrespective of the linear distortion model, which improves the quality of DEM vertical comparison accuracy significantly and is suitable and helpful for DEM quality assessment. A systematic TomoSAR algorithm and method have been established, tested, analysed and demonstrated for various applications (urban buildings, bridges, dams) to achieve better 3D & 4D tomographic SAR imaging results. These include applying Cosmo-Skymed X band single-polarisation data over the Zipingpu dam, Dujiangyan, Sichuan, China, to map topography; and using ALOS L band data in the San Francisco Bay region to map urban building and bridge. A new ionospheric correction method based on the tile method employing IGS TEC data, a split-spectrum and an ionospheric model via least squares are developed to correct ionospheric distortion to improve the accuracy of 3D & 4D tomographic SAR imaging. Meanwhile, a pixel by pixel orbit baseline estimation method is developed to address the research gaps of baseline estimation for 3D & 4D spaceborne SAR tomography imaging. Moreover, a SAR tomography imaging algorithm and a differential tomography four-dimensional SAR imaging algorithm based on compressive sensing, SAR interferometry phase (InSAR) calibration reference to DEM with DEM error correction, a new phase error calibration and compensation algorithm, based on PS, SVD, PGA, weighted least squares and minimum entropy, are developed to obtain accurate 3D & 4D tomographic SAR imaging results. The new baseline estimation method and consequent TomoSAR processing results showed that an accurate baseline estimation is essential to build up the TomoSAR model. After baseline estimation, phase calibration experiments (via FFT and Capon method) indicate that a phase calibration step is indispensable for TomoSAR imaging, which eventually influences the inversion results. A super-resolution reconstruction CS based study demonstrates X band data with the CS method does not fit for forest reconstruction but works for reconstruction of large civil engineering structures such as dams and urban buildings. Meanwhile, the L band data with FFT, Capon and the CS method are shown to work for the reconstruction of large manmade structures (such as bridges) and urban buildings

Remote Sensing methods for power line corridor surveys

AbstractTo secure uninterrupted distribution of electricity, effective monitoring and maintenance of power lines are needed. This literature review article aims to give a wide overview of the possibilities provided by modern remote sensing sensors in power line corridor surveys and to discuss the potential and limitations of different approaches. Monitoring of both power line components and vegetation around them is included. Remotely sensed data sources discussed in the review include synthetic aperture radar (SAR) images, optical satellite and aerial images, thermal images, airborne laser scanner (ALS) data, land-based mobile mapping data, and unmanned aerial vehicle (UAV) data. The review shows that most previous studies have concentrated on the mapping and analysis of network components. In particular, automated extraction of power line conductors has achieved much attention, and promising results have been reported. For example, accuracy levels above 90% have been presented for the extraction of conductors from ALS data or aerial images. However, in many studies datasets have been small and numerical quality analyses have been omitted. Mapping of vegetation near power lines has been a less common research topic than mapping of the components, but several studies have also been carried out in this field, especially using optical aerial and satellite images. Based on the review we conclude that in future research more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way. Knowledge in related fields, such as vegetation monitoring from ALS, SAR and optical image data should be better exploited to develop useful monitoring approaches. Special attention should be given to rapidly developing remote sensing techniques such as UAVs and laser scanning from airborne and land-based platforms. To demonstrate and verify the capabilities of automated monitoring approaches, large tests in various environments and practical monitoring conditions are needed. These should include careful quality analyses and comparisons between different data sources, methods and individual algorithms