Download or read book Computational Imaging Systems for High speed Adaptive Sensing Applications written by Yangyang Sun and published by . This book was released on 2019 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: Range Imaging, Computational Imaging, Adaptive Sensing, Sensor Placement

Download or read book Computational Optical Imaging written by Zhengjun Liu and published by Springer Nature. This book was released on with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Imaging written by Ayush Bhandari and published by MIT Press. This book was released on 2022-10-25 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and up-to-date textbook and reference for computational imaging, which combines vision, graphics, signal processing, and optics. Computational imaging involves the joint design of imaging hardware and computer algorithms to create novel imaging systems with unprecedented capabilities. In recent years such capabilities include cameras that operate at a trillion frames per second, microscopes that can see small viruses long thought to be optically irresolvable, and telescopes that capture images of black holes. This text offers a comprehensive and up-to-date introduction to this rapidly growing field, a convergence of vision, graphics, signal processing, and optics. It can be used as an instructional resource for computer imaging courses and as a reference for professionals. It covers the fundamentals of the field, current research and applications, and light transport techniques. The text first presents an imaging toolkit, including optics, image sensors, and illumination, and a computational toolkit, introducing modeling, mathematical tools, model-based inversion, data-driven inversion techniques, and hybrid inversion techniques. It then examines different modalities of light, focusing on the plenoptic function, which describes degrees of freedom of a light ray. Finally, the text outlines light transport techniques, describing imaging systems that obtain micron-scale 3D shape or optimize for noise-free imaging, optical computing, and non-line-of-sight imaging. Throughout, it discusses the use of computational imaging methods in a range of application areas, including smart phone photography, autonomous driving, and medical imaging. End-of-chapter exercises help put the material in context.

Download or read book Computational Photography written by Saghi Hajisharif and published by Linköping University Electronic Press. This book was released on 2020-02-18 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: The introduction and recent advancements of computational photography have revolutionized the imaging industry. Computational photography is a combination of imaging techniques at the intersection of various fields such as optics, computer vision, and computer graphics. These methods enhance the capabilities of traditional digital photography by applying computational techniques both during and after the capturing process. This thesis targets two major subjects in this field: High Dynamic Range (HDR) image reconstruction and Light Field (LF) compressive capturing, compression, and real-time rendering. The first part of the thesis focuses on the HDR images that concurrently contain detailed information from the very dark shadows to the brightest areas in the scenes. One of the main contributions presented in this thesis is the development of a unified reconstruction algorithm for spatially variant exposures in a single image. This method is based on a camera noise model, and it simultaneously resamples, reconstructs, denoises, and demosaics the image while extending its dynamic range. Furthermore, the HDR reconstruction algorithm is extended to adapt to the local features of the image, as well as the noise statistics, to preserve the high-frequency edges during reconstruction. In the second part of this thesis, the research focus shifts to the acquisition, encoding, reconstruction, and rendering of light field images and videos in a real-time setting. Unlike traditional integral photography, a light field captures the information of the dynamic environment from all angles, all points in space, and all spectral wavelength and time. This thesis employs sparse representation to provide an end-to-end solution to the problem of encoding, real-time reconstruction, and rendering of high dimensional light field video data sets. These solutions are applied on various types of data sets, such as light fields captured with multi-camera systems or hand-held cameras equipped with micro-lens arrays, and spherical light fields. Finally, sparse representation of light fields was utilized for developing a single sensor light field video camera equipped with a color-coded mask. A new compressive sensing model is presented that is suitable for dynamic scenes with temporal coherency and is capable of reconstructing high-resolution light field videos.

Download or read book Physical Optics Based Computational Imaging Systems written by Stephen Joseph Olivas and published by . This book was released on 2015 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is an ongoing demand on behalf of the consumer, medical and military industries to make lighter weight, higher resolution, wider field-of-view and extended depth-of-focus cameras. This leads to design trade-offs between performance and cost, be it size, weight, power, or expense. This has brought attention to finding new ways to extend the design space while adhering to cost constraints. Extending the functionality of an imager in order to achieve extraordinary performance is a common theme of computational imaging, a field of study which uses additional hardware along with tailored algorithms to formulate and solve inverse problems in imaging. This dissertation details four specific systems within this emerging field: a Fiber Bundle Relayed Imaging System, an Extended Depth-of-Focus Imaging System, a Platform Motion Blur Image Restoration System, and a Compressive Imaging System. The Fiber Bundle Relayed Imaging System is part of a larger project, where the work presented in this thesis was to use image processing techniques to mitigate problems inherent to fiber bundle image relay and then, form high-resolution wide field-of-view panoramas captured from multiple sensors within a custom state-of-the-art imager. The Extended Depth-of-Focus System goals were to characterize the angular and depth dependence of the PSF of a focal swept imager in order to increase the acceptably focused imaged scene depth. The goal of the Platform Motion Blur Image Restoration System was to build a system that can capture a high signal-to-noise ratio (SNR), long-exposure image which is inherently blurred while at the same time capturing motion data using additional optical sensors in order to deblur the degraded images. Lastly, the objective of the Compressive Imager was to design and build a system functionally similar to the Single Pixel Camera and use it to test new sampling methods for image generation and to characterize it against a traditional camera. These computational imaging systems share a common theme in that they seek to accomplish camera designs that meet more demanding system requirements through the use of additional measurements made possible by hardware modifications, while relying on modeling and computational methods in order to provide valuable scene information.

Download or read book Design and Implementation of Real Time Multi Sensor Vision Systems written by Vladan Popovic and published by Springer. This book was released on 2017-07-03 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the design of multi-camera systems and their application to fields such as the virtual reality, gaming, film industry, medicine, automotive industry, drones, etc. The authors cover the basics of image formation, algorithms for stitching a panoramic image from multiple cameras, and multiple real-time hardware system architectures, in order to have panoramic videos. Several specific applications of multi-camera systems are presented, such as depth estimation, high dynamic range imaging, and medical imaging.

Download or read book Computational Imaging and Its Application written by Helen Peng and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Traditional optical imaging systems have constrained angular and spatial resolution, depth of field, field of view, tolerance to aberrations and environmental conditions, and other image quality limitations. Computational imaging provided an opportunity to create new functionality and improve the performance of imaging systems by encoding the information optically and decoding it computationally. The design of a computational imaging system balances hardware costs and the accuracy and complexity of the algorithms. In this thesis, two computational imaging systems are presented: Randomized Aperture Imaging and Laser Suppression Imaging. The former system increases the angular resolution of telescopes by replacing a continuous primary mirror with an array of light-weight small mirror elements, which potentially allows telescopes to have very large diameter at a reduced cost. The latter imaging system protects camera sensors from laser effects such as dazzle by use of a phase coded pupil plane mask. Machine learning and deep learning based algorithms were investigated to restore high-fidelity images from the coded acquisitions. The proposed imaging systems are verified by experiment and numerical modeling, and improved performances are demonstrated in comparison with the state-of-the-art."--Abstract.

Download or read book Computational Color Imaging written by Shoji Tominaga and published by Springer. This book was released on 2013-03-02 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th Computational Color Imaging Workshop, CCIW 2013, held in Chiba, Japan, in March 2013. The 21 revised full papers, presented together with 4 invited papers, were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on color image perception; color combination; multi-spectral image analysis and rendering; color image detection and classification; color image features; and color image filtering and enhancement.

Download or read book Architectures for Compressive Imaging with Applications in Sensor Networks Adaptive Object Reconstruction and Motion Detection written by and published by . This book was released on 2010 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational imaging becomes a cutting edge research area by incorporating signal/image processing as an inherent part of an imaging system. Its civil and military applications include surveillance, automobile, and medical health. The newest branch of computational imaging, compressive imaging emerged in several years back. In-stead of making measurement for each individual object pixel, compressive imaging directly making compressed measurements using optical/opto-electronic devices in data acquisition process. These compressed measurements referred to as features are linear combinations of object pixels weighted by transformation bases. Usingvarious types of signal processing techniques, features are processed for the imaging system final tasks such as reconstruction, detection, and recognition. In this dissertation, three compressive imaging implementation architectures, sequential, parallel, and photon-sharing architectures, are analyzed. Two kinds of applications, object reconstruction and motion detections, are studied using projections including PC (Principal Component), Hadamard, DCT (Discrete Cosine Transformation), Gabor, and random projection. Linear and/or nonlinear algorithms are used for static and adaptive measurements. A webcam based multi-sensor network and a DMD based single detector imaging system demonstrate the dissertation work.

Download or read book Optical Compressive Imaging written by Adrian Stern and published by CRC Press. This book was released on 2016-11-17 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dedicated overview of optical compressive imaging addresses implementation aspects of the revolutionary theory of compressive sensing (CS) in the field of optical imaging and sensing. It overviews the technological opportunities and challenges involved in optical design and implementation, from basic theory to optical architectures and systems for compressive imaging in various spectral regimes, spectral and hyperspectral imaging, polarimetric sensing, three-dimensional imaging, super-resolution imaging, lens-free, on-chip microscopy, and phase sensing and retrieval. The reader will gain a complete introduction to theory, experiment, and practical use for reducing hardware, shortening image scanning time, and improving image resolution as well as other performance parameters. Optics practitioners and optical system designers, electrical and optical engineers, mathematicians, and signal processing professionals will all find the book a unique trove of information and practical guidance. Delivers the first book on compressed sensing dealing with system development for a wide variety of optical imaging and sensing applications. Covers the fundamentals of CS theory, including noise and algorithms, as well as basic design approaches for data acquisition in optics. Addresses the challenges of implementing compressed sensing theory in the context of different optical imaging designs, from 3D imaging to tomography and microscopy. Provides an essential resource for the design of new and improved devices with improved image quality and shorter acquisition times. Adrian Stern, PhD, is associate professor and head of the Electro-Optical Engineering Unit at Ben-Gurion University of the Negev, Israel. He is an elected Fellow of SPIE.

Download or read book Computational Imaging and Inverse Techniques for High resolution and Instantaneous Spectral Imaging written by and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book High Performance Computing in Remote Sensing written by Antonio J. Plaza and published by CRC Press. This book was released on 2007-10-18 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solutions for Time-Critical Remote Sensing Applications The recent use of latest-generation sensors in airborne and satellite platforms is producing a nearly continual stream of high-dimensional data, which, in turn, is creating new processing challenges. To address the computational requirements of time-critical applications, researchers

Download or read book Novel Methods in Computational Imaging with Applications in Remote Sensing written by and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract : This dissertation is devoted to novel computational imaging methods with applications in remote sensing. Computational imaging methods are applied to three distinct applications including imaging and detection of buried explosive hazards utilizing array radar, high resolution imaging of satellites in geosynchronous orbit utilizing optical hypertelescope arrays, and characterization of atmospheric turbulence through multi-frame blind deconvolution utilizing conventional optical digital sensors. The first application considered utilizes a radar array employed as a forward looking ground penetrating radar system with applications in explosive hazard detection. A penalized least squares technique with sparsity-inducing regularization is applied to produce imagery, which is consistent with the expectation that objects are sparsely populated but extended with respect to the pixel grid. Additionally, a series of pre-processing steps is demonstrated which result in a greatly reduced data size and computational cost. Demonstrations of the approach are provided using experimental data and results are given in terms of signal to background ratio, image resolution, and relative computation time. The second application involves a sparse-aperture telescope array configured as a hypertelescope with applications in long range imaging. The penalized least squares technique with sparsity-inducing regularization is adapted and applied to this very different imaging modality. A comprehensive study of the algorithm tuning parameters is performed and performance is characterized using the Structure Similarity Metric (SSIM) to maximize image quality. Simulated measurements are used to show that imaging performance achieved using the pro- posed algorithm compares favorably in comparison to conventional Richardson-Lucy deconvolution. The third application involves a multi-frame collection from a conventional digital sensor with the primary objective of characterizing the atmospheric turbulence in the medium of propagation. In this application a joint estimate of the image is obtained along with the Zernike coefficients associated with the atmospheric PSF at each frame, and the Fried parameter r0 of the atmosphere. A pair of constraints are applied to a penalized least squares objective function to enforce the theoretical statistics of the set of PSF estimates as a function of r0. Results of the approach are shown with both simulated and experimental data and demonstrate excellent agreement between the estimated r0 values and the known or measured r0 values respectively.

Download or read book NASA Technical Memorandum written by and published by . This book was released on 1989 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Image Processing Technologies written by Kiyoharu Aizawa and published by CRC Press. This book was released on 2004-03 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Showcasing the most influential developments, experiments, and architectures impacting the digital, surveillance, automotive, industrial, and medical sciences, this text/reference tracks the evolution and advancement of CVIP technologies - examining methods and algorithms for image analysis, optimization, segmentation, and restoration.

Download or read book Integrated Computational Imaging Systems written by Joseph Van der Gracht and published by . This book was released on 2002 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digest and expanded papers from a November 2001 meeting offer definitions of integrated imaging, present examples of imaging systems, and describe concepts from information theory as they apply to the analysis and design of imaging systems. Material is in sections on key topics, wavefront coding, computational microscopes, information theory and design, imaging systems, implementation, hyperspectral systems, and analysis and situation. Three-dimensional coherence imaging in the Fresnel domain, spatial tomography and coherence microscopy, and modeling of sparse aperture telescope image quality are some of the areas discussed. Annotation copyrighted by Book News, Inc., Portland, OR

Download or read book Design and Analysis of Integrated Computational Imaging Systems written by Wai-San Chan and published by Open Dissertation Press. This book was released on 2017-01-27 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation, "Design and Analysis of Integrated Computational Imaging Systems" by Wai-san, Chan, 陳慧珊, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled "Design and Analysis of Integrated Computational Imaging Systems" Submitted by Chan Wai San for the degree of Master of Philosophy at The University of Hong Kong in September 2007 In an integrated computational imaging system, the physical system which gen- erates the image signal, data collection and post-processing are integrally incor- porated in the design process. This system usually does not deliver a visually pleasingimageatthefirststep. Instead, itproducesanintermediateimagewhich, although not visually attractive, preserves all the useful information of the ob- ject. Post-detection computation of the intermediate image will lead to a better final image. The motivation of integrated computational imaging systems is that through the concurrent design and joint optimization of signal generation, data collection and post-processing, performance and efficiency can be enhanced. This dissertation investigates two integrated computational imaging systems. The first is a compound-eye imaging (CEI) system, and the second is a magnetic resonance imaging (MRI) system. The CEI system is a non-conventional optical imagingsystemwhichismadeverycompactbytheutilizationofanarrayofsmall lenses in image formation. The array of small lenses forms an intermediate imagewhich consists of multiple low-resolution sub-images of the object. The final image is recovered by post-processing of the multiple sub-images. Low resolution and poor quality of the reconstructed image are the main problems of a CEI system. In this study, we use our own super-resolution algorithm for image reconstruction for a CEI system to enhance the quality and resolution of the reconstructed image. The capability of the system is further enhanced by the incorporation of a phase-mask array to increase its depth of field. A virtual CEI system was built to facilitate the investigation. The feasibilities of our proposed methods are verified by simulation experiments with the virtual system. The second part of the study investigates an MRI system. MRI is a powerful medical imaging module. However, the long scan time is an impediment to its use in certain applications. This study examines the feasibility and efficiency of applying compressive sensing (CS) in MRI to reduce the scan time. It also explores how k-space data acquisitions affect the performance of CS on MRI reconstruction. The analysis is based on simulation experiments. The study's findings indicate that the conventional radial and spiral trajectories are both robustk-spacemeasurementschemeswhichcanworkwellwithCSreconstruction to give high quality MR images from a highly incomplete set (just around 13%) of k-space data. An abstract of exactly 383 words DOI: 10.5353/th_b3896035 Subjects: Imaging systems - Design and construction Image processing - Digital techniques Magnetic resonance imaging