Characteristics Of Image Sensors Research Articles

Influence of Flight Height and Image Sensor on the Quality of the UAS Orthophotos for Cadastral Survey Purposes

The possibility of using unmanned aircraft systems (UAS) for cadastral survey purposes was investigated in this research. A study site consisting of 26 ground control points (GCP) and checkpoints (CP) was established. The study site was first measured by the classical methods of geodetic surveying, i.e., by the polar method using a total station. After that, all points were additionally measured by the Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) method. The GNSS RTK method was used to determine the coordinates of all points in the official map projection of Croatia, HTRS96/TM, while the polar method was used to increase the positional “strength” of points in all directions, i.e., to improve the relative accuracy between them. Using UASs with different image sensor characteristics, the study site was measured by an aerial photogrammetry method at different flight heights with the purpose of obtaining a high-quality digital orthophoto plan (DOF). The absolute orientation of the model was performed using the external orientation data of each digital image based on GNSS and Inertial Measurement Unit (IMU) UAS’s sensors, as well as using GCPs. Achieved precision of obtained DOF, as well as accuracy analysis of aerial photogrammetry was performed by considering the adjusted survey data collected by classical and GNSS RTK methods as true values and comparing them with the coordinates obtained by the aerial photogrammetry method from DOFs. Based on the achieved results and conclusions obtained from the study site, the second field test was performed above a small settlement which served as an area for cadastral survey using the UAS and GNSS RTK method. Again, precision and accuracy were determined, based on which we derived recommendations and conclusions for using UASs for cadastral survey purposes.

Automatic Generation of Synthetic Colonoscopy Videos for Domain Randomization

Abstract An increasing number of colonoscopic guidance and assistance systems rely on machine learning algorithms which require a large amount of high-quality training data. In order to ensure high performance, the latter has to resemble a substantial portion of possible configurations. This particularly addresses varying anatomy, mucosa appearance and image sensor characteristics which are likely deteriorated by motion blur and inadequate illumination. The limited amount of readily available training data hampers to account for all of these possible configurations which results in reduced generalization capabilities of machine learning models. We propose an exemplary solution for synthesizing colonoscopy videos with substantial appearance and anatomical variations which enables to learn discriminative domain-randomized representations of the interior colon while mimicking real-world settings.

Functional Materials and Devices for XR (VR/AR/MR) Applications

Functional Materials and Devices for XR (VR/AR/MR) Applications

ВІДНОВЛЕННЯ ІНФОРМАЦІЙНИХ ХАРАКТЕРИСТИК ОБ’ЄКТІВ ЗА БАГАТОСПЕКТРАЛЬНИМИ ЦИФРОВИМИ ЗОБРАЖЕННЯМИ ДИСТАНЦІЙНОГО ЗОНДУВАННЯ

Запропоновано новий метод визначення відбивальної спроможності (власної яскравості) матеріальних об’єктів за їх ізопланатичними багатоспектральними зображеннями, зафіксованими в оптичному, інфрачервоному та мікрохвильовому діапазонах електромагнітного проміння – носія видової інформації. Розподіли яскравості таких зображень подані у вигляді згортки власної яскравості поданих на них об’єктів та апаратної функції датчика зображення. Пропонований метод базується на аналізі спектральних представлень розподілів яскравості зображень в області просторових частот, перетворення у яку реалізовано двовимірним дискретним перетворенням Фур’є зазначеної згортки. В якості моделі передатних характеристик датчиків зображень прийняті низькочастотні просторові фільтри, які моделюють датчики зображень у вигляді фокусуючи систем, з частотами зрізу, обернено пропорційними довжині хвилі проміння – носія видової інформації. За інформаційний носій представлень цифрових багатоспектральних зображень в області просторових частот прийнятий двовимірний масив у вигляді конкатенації векторів, які подають розподіли просторових спектрів Фур’є функцій яскравості окремих спектральних каналів. Відновлення власної яскравості відображених об’єктів здійснено в термінах загальної теорії лінійних вимірювань і виконане шляхом побудови лінійного оператора, який реалізує концепцію «ідеального приладу», який компенсує вплив апаратної функції датчика зображень. Власне реконструкція просторових розподілів яскравості здійснена оберненим двовимірним дискретним перетворенням Фур’є в області просторових частот. Дано ентропійну інтерпретацію запропонованого методу як способу фільтрації інформаційних складових багатоспектральних цифрових зображень, несуттєвих для їхнього тематичного аналізу, за умови статистичної незалежності просторових спектрів зафіксованих зображень та частотної передатної характеристики датчика видової інформації і наведені відповідні кількісні оцінки. Показано, що пропонований метод забезпечує високий рівень структурної схожості функцій розподілу яскравості первинних (безпосередньо зафіксованих) та реконструйованих зображень власної яскравості спектральних каналів.

A posteriori correction of camera characteristics from large image data sets.

Large datasets are emerging in many fields of image processing including: electron microscopy, light microscopy, medical X-ray imaging, astronomy, etc. Novel computer-controlled instrumentation facilitates the collection of very large datasets containing thousands of individual digital images. In single-particle cryogenic electron microscopy (“cryo-EM”), for example, large datasets are required for achieving quasi-atomic resolution structures of biological complexes. Based on the collected data alone, large datasets allow us to precisely determine the statistical properties of the imaging sensor on a pixel-by-pixel basis, independent of any “a priori” normalization routinely applied to the raw image data during collection (“flat field correction”). Our straightforward “a posteriori” correction yields clean linear images as can be verified by Fourier Ring Correlation (FRC), illustrating the statistical independence of the corrected images over all spatial frequencies. The image sensor characteristics can also be measured continuously and used for correcting upcoming images.

이미지 센서 및 모듈의 표준 영상 취득 테스트

일반적으로 이미지 센서 및 모듈의 영상 취득 특성 테스트는 테스트할 이미지 센서 및 모듈의 특성, 해당 센서 및 모듈이 장착될 기기의 사용 목적, 테스트 장비의 기능 등에 따라 세부적인 내용은 많이 다르지만, 산업체에서 자주 사용되어 사실상 표준으로 굳어진 몇몇 테스트는 불량을 판별하기 위한 기준치 등 몇몇 파라미터만 다르게 하여 대부분의 이미지 센서 및 모듈에 적용된다. 본 논문에서는 이들 중에서 대표적인 11개 테스트를 자세히 설명하고, 이를 단일 프레임워크 내에서 간단하고 명확한 형태로 표기하여 테스트 프로그램을 작성할 때의 오류와 노력을 크게 줄이도록 한다. In general, image acquisition characteristics tests of image sensors and modules vary widely according to the characteristics of image sensors and modules under test, the application purpose of target devices where image sensors and modules are mounted, and the functions of test equipments. However, some de facto standard tests are frequently used in industry fields. They differ only in several parameters e.g. thresholds for fault detection, and they can be applied to most image sensors and modules. In this paper, 11 typical tests are explained in detail, and they are described in a simple and clear form under single framework, which significantly reduces errors and saves efforts.

Fundamentals of Ion Implantation Technologies for Image Sensing Devices

Ion implantation is one of the weightiest operations for image sensing device fabrication. In this paper several impacts of ion implantation for characteristics of image sensors are considered. Among metal contamination, implant damages, micro uniformity and so on, metal contamination is the most important issue for reduction of dark current and white blemish in image pixels and an immediate target of metal contamination level of less than 1E-9 cm-2 at popular implant conditions is successfully achieved. Ultra-high energy implants of 5MeV boron and over 8MeV phosphorous and arsenic for Rp deeper than 3 mm are very attractive to obtain superior characteristics of high-end image sensing devices. Implant damage, scan overlap, implant angle accuracy, and low-energy medium-dose implant are also discussed.

A Practical Approach Based on Analytic Deformable Algorithm for Scenic Image Registration

BackgroundImage registration is to produce an entire scene by aligning all the acquired image sequences. A registration algorithm is necessary to tolerance as much as possible for intensity and geometric variation among images. However, captured image views of real scene usually produce unexpected distortions. They are generally derived from the optic characteristics of image sensors or caused by the specific scenes and objects.Methods and FindingsAn analytic registration algorithm considering the deformation is proposed for scenic image applications in this study. After extracting important features by the wavelet-based edge correlation method, an analytic registration approach is then proposed to achieve deformable and accurate matching of point sets. Finally, the registration accuracy is further refined to obtain subpixel precision by a feature-based Levenberg-Marquardt (FLM) method. It converges evidently faster than most other methods because of its feature-based characteristic.ConclusionsWe validate the performance of proposed method by testing with synthetic and real image sequences acquired by a hand-held digital still camera (DSC) and in comparison with an optical flow-based motion technique in terms of the squared sum of intensity differences (SSD) and correlation coefficient (CC). The results indicate that the proposed method is satisfactory in the registration accuracy and quality of DSC images.

Registration Accuracy and Quality of Real-Life Images

BackgroundA common registration problem for the application of consumer device is to align all the acquired image sequences into a complete scene. Image alignment requires a registration algorithm that will compensate as much as possible for geometric variability among images. However, images captured views from a real scene usually produce different distortions. Some are derived from the optic characteristics of image sensors, and others are caused by the specific scenes and objects.Methodology/Principal FindingsAn image registration algorithm considering the perspective projection is proposed for the application of consumer devices in this study. It exploits a multiresolution wavelet-based method to extract significant features. An analytic differential approach is then proposed to achieve fast convergence of point matching. Finally, the registration accuracy is further refined to obtain subpixel precision by a feature-based modified Levenberg-Marquardt method. Due to its feature-based and nonlinear characteristic, it converges considerably faster than most other methods. In addition, vignette compensation and color difference adjustment are also performed to further improve the quality of registration results.Conclusions/SignificanceThe performance of the proposed method is evaluated by testing the synthetic and real images acquired by a hand-held digital still camera and in comparison with two registration techniques in terms of the squared sum of intensity differences (SSD) and correlation coefficient (CC). The results indicate that the proposed method is promising in registration accuracy and quality, which are statistically significantly better than other two approaches.

Real-time digital signal processing for live electro-optic imaging

We present an imaging system that enables real-time magnitude and phase detection of modulated signals and its application to a Live Electro-optic Imaging (LEI) system, which realizes instantaneous visualization of RF electric fields. The real-time acquisition of magnitude and phase images of a modulated optical signal at 5 kHz is demonstrated by imaging with a Si-based high-speed CMOS image sensor and real-time signal processing with a digital signal processor. In the LEI system, RF electric fields are probed with light via an electro-optic crystal plate and downconverted to an intermediate frequency by parallel optical heterodyning, which can be detected with the image sensor. The artifacts caused by the optics and the image sensor characteristics are corrected by image processing. As examples, we demonstrate real-time visualization of electric fields from RF circuits.

Degradation Behavior and Damage Mechanisms of CCD Image Sensor With Deep-UV Laser Radiation

As the deep-ultraviolet (DUV) laser technology continues to mature, an increasing number of industrial applications is shifting to intense DUV radiation sources. This trend necessitates the development of DUV sensitive charge-coupled device (CCD) cameras to provide imaging capability for process control and inspection purposes. In this paper, we examine the effects of DUV laser radiation on CCD image sensor characteristics and the mechanisms responsible for DUV laser damage in CCDs. When samples of thinned front-illuminated linescan CCD sensors are exposed to F/sub 2/(/spl lambda/=157 nm) excimer laser radiation, fluctuation in the extrinsic quantum efficiency (QE) and a substantial upsurge in the dark current density are observed as a function of exposure dose. The visible QE, dark current, and charge conversion efficiency (CCE) are also permanently altered by the DUV irradiation. These instabilities can be attributed to a variety of UV-induced effects that modify the optical and electrical properties of the SiO/sub 2/ layer and Si-SiO/sub 2/ interface, resulting in temporary and permanent shifts in CCD performance. Optimization of the overlying oxide thickness and the Si-SiO/sub 2/ interface quality are necessary in order to realize CCD sensors with the desired performance, radiation tolerance and stability at DUV wavelengths.