Relevant bibliographies by topics / Image Processing Pipelines

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Image Processing Pipelines'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 September 2023

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Journal articles on the topic "Image Processing Pipelines"

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Gillmann, Christina, Pablo Arbelaez, Jose Hernandez, Hans Hagen, and Thomas Wischgoll. "An Uncertainty-Aware Visual System for Image Pre-Processing." Journal of Imaging 4, no. 9 (2018): 109. http://dx.doi.org/10.3390/jimaging4090109.

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Due to image reconstruction process of all image capturing methods, image data is inherently affected by uncertainty. This is caused by the underlying image reconstruction model, that is not capable to map all physical properties in its entirety. In order to be aware of these effects, image uncertainty needs to be quantified and propagated along the entire image processing pipeline. In classical image processing methodologies, pre-processing algorithms do not consider this information. Therefore, this paper presents an uncertainty-aware image pre-processing paradigm, that is aware of the input
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Tseng, Ethan, Yuxuan Zhang, Lars Jebe, et al. "Neural Photo-Finishing." ACM Transactions on Graphics 41, no. 6 (2022): 1–15. http://dx.doi.org/10.1145/3550454.3555526.

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Image processing pipelines are ubiquitous and we rely on them either directly, by filtering or adjusting an image post-capture, or indirectly, as image signal processing (ISP) pipelines on broadly deployed camera systems. Used by artists, photographers, system engineers, and for downstream vision tasks, traditional image processing pipelines feature complex algorithmic branches developed over decades. Recently, image-to-image networks have made great strides in image processing, style transfer, and semantic understanding. The differentiable nature of these networks allows them to fit a large c
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Mullapudi, Ravi Teja, Andrew Adams, Dillon Sharlet, Jonathan Ragan-Kelley, and Kayvon Fatahalian. "Automatically scheduling halide image processing pipelines." ACM Transactions on Graphics 35, no. 4 (2016): 1–11. http://dx.doi.org/10.1145/2897824.2925952.

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Berg, Steffen, Nishank Saxena, Majeed Shaik, and Chaitanya Pradhan. "Generation of ground truth images to validate micro-CT image-processing pipelines." Leading Edge 37, no. 6 (2018): 412–20. http://dx.doi.org/10.1190/tle37060412.1.

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Digital rock technology and pore-scale physics have become increasingly relevant topics in a wide range of porous media with important applications in subsurface engineering. This technology relies heavily on images of pore space and pore-level fluid distribution determined by X-ray microcomputed tomography (micro-CT). Digital images of pore space (or pore-scale fluid distribution) are typically obtained as gray-level images that first need to be processed and segmented to obtain the binary images that uniquely represent rock and pore (including fluid phases). This processing step is not trivi
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Raju, Rajeswari, Tomas Maul, and Andrzej Bargiela. "New image processing pipelines for membrane detection." Journal of the Institute of Industrial Applications Engineers 3, no. 1 (2015): 15–23. http://dx.doi.org/10.12792/jiiae.3.15.

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Garcia, Lionel J., Mathilde Timmermans, Francisco J. Pozuelos, et al. "prose: a python framework for modular astronomical images processing." Monthly Notices of the Royal Astronomical Society 509, no. 4 (2021): 4817–28. http://dx.doi.org/10.1093/mnras/stab3113.

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ABSTRACT To reduce and analyse astronomical images, astronomers can rely on a wide range of libraries providing low-level implementations of legacy algorithms. However, combining these routines into robust and functional pipelines requires a major effort that often ends up in instrument-specific and poorly maintainable tools, yielding products that suffer from a low level of reproducibility and portability. In this context, we present prose, a python framework to build modular and maintainable image processing pipelines. Built for astronomy, it is instrument-agnostic and allows the constructio
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Aranda, Luis, Pedro Reviriego, and Juan Maestro. "Protecting Image Processing Pipelines against Configuration Memory Errors in SRAM-Based FPGAs." Electronics 7, no. 11 (2018): 322. http://dx.doi.org/10.3390/electronics7110322.

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Image processing systems are widely used in space applications, so different radiation-induced malfunctions may occur in the system depending on the device that is implementing the algorithm. SRAM-based FPGAs are commonly used to speed up the image processing algorithm, but then the system could be vulnerable to configuration memory errors caused by single event upsets (SEUs). In those systems, the captured image is streamed pixel by pixel from the camera to the FPGA. Certain local operations such as median or rank filters need to process the image locally instead of pixel by pixel, so some pa
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Ramos, Vitor S., Luiz Gonzaga De Q. Silveira Junior, and Luiz Felipe De Q. Silveira. "Single Image Highlight Removal for Real-Time Image Processing Pipelines." IEEE Access 8 (2020): 3240–54. http://dx.doi.org/10.1109/access.2019.2963037.

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Melet, O., D. Youssefi, C. L'Helguen, et al. "CO3D MISSION DIGITAL SURFACE MODEL PRODUCTION PIPELINE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (August 12, 2020): 143–48. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-143-2020.

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Abstract. Earth Observation (EO) remote sensing missions are producing an increasing volume of data due to higher spatial and spectral resolutions, and higher frequency of acquisitions. Thus, in order to prepare the future of image processing pipelines, CNES has carried out Research & Development studies related to the use of Big Data and Cloud technologies for image processing chains made. Since mid-2019, CNES in partnership with Airbus Defense & Space, has started a new High Resolution Optical EO mission dedicated to very high resolution 3D observation called CO3D (“Constella
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Wang, Xian Lun, Li Li, and Yu Xia Cui. "Detection and Location of Underwater Pipeline Based on Mathematical Morphology for an AUV." Key Engineering Materials 561 (July 2013): 591–96. http://dx.doi.org/10.4028/www.scientific.net/kem.561.591.

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Underwater pipelines of oil and gas need periodic inspection to prevent damage due to the biological activity of water, turbulent current and tidal abrasion. Currently, vision-based autonomous underwater vehicle plays an important role in this field. A system has been designed to help an autonomous vehicle in sea-bottom survey operation. Image understanding and object recognition directly affect the accuracy of inspection. An image smoothing method based on mathematical morphology is proposed. The disturbances on acquired images caused by the motion are partially removed. A series of algorithm
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Dissertations / Theses on the topic "Image Processing Pipelines"

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Gharbi, Michael (Michael Yanis). "Learning efficient image processing pipelines." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120437.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages [125]-138).<br>The high resolution of modern cameras puts significant performance pressure on image processing pipelines. Tuning the parameters of these pipelines for speed is subject to stringent image quality constraints and requires significant efforts from skilled programmers. Because quality is driven by perceptual factors with which most quantitative image metrics correlate poorly, de
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Fouquet, Clément. "Aide à la détection et à la reconnaissance de défauts structurels dans les pipelines par analyse automatique des images XtraSonic." Thesis, Cergy-Pontoise, 2014. http://www.theses.fr/2014CERG0729/document.

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TRAPIL est une société Française ayant à charge l'exploitation et l'entretien de pipelines d'hydrocarbures. L'entretien de pipelines enterrés nécessite le passage de racleurs équipés de sondes ultrasons réalisant une cartographie de la structure du pipeline, qui est ensuite analysée à la main afin de détecter et d'identifier les différents défauts pouvant apparaître ou évoluer.L'objectif de ce travail de thèse est d'apporter une solution algorithmique permettant d'accélérer et de compléter le travail des analystes à l'aide des méthodes modernes de traitement d'images et du signal.Notre approch
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Hall, Arthur Daniel. "Pipelined image processing for pattern recognition." Thesis, University of Cambridge, 1992. https://www.repository.cam.ac.uk/handle/1810/251523.

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Ali, Faridah M. "Parallel pipelined VLSI arrays for real-time image processing." Diss., Virginia Polytechnic Institute and State University, 1988. http://hdl.handle.net/10919/49914.

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Real-time image processing involves processing a wide spectrum of algorithms on huge data sets. Processing at the pixel data rate demands more powerful parallel machines than those developed for conventional image processing. This research takes advantage of current VLSI technology to examine a new approach for processing arbitrary algorithms at real-time data rate. It is based on embedding the algorithms, expressed by their dependency graphs, into two dimensional regularly connected processing arrays. Each node in a graph represents an operation which can be processed by an individual proces
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Singnoo, Jakkarin. "A simplified HDR image processing pipeline for digital photography." Thesis, University of East Anglia, 2012. https://ueaeprints.uea.ac.uk/41945/.

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High Dynamic Range (HDR) imaging has revolutionized the digital imaging. It allows capture, storage, manipulation, and display of full dynamic range of the captured scene. As a result, it has spawned whole new possibilities for digital photography, from photorealistic to hyper-real. With all these advantages, the technique is expected to replace the conventional 8-bit Low Dynamic Range (LDR) imaging in the future. However, HDR results in an even more complex imaging pipeline including new techniques for capturing, encoding, and displaying images. The goal of this thesis is to bridge the gap be
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Sheblee, Jafer Sadeg. "A hierarchical pipeline processor for image analysis." Thesis, University of Newcastle Upon Tyne, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239614.

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Woods, Bronwyn Lewisia. "Toward a Processing Pipeline for Two-photon Calcium Imaging of Neural Populations." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/393.

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Two-photon calcium imaging (TPCI) is a functional neuroimaging technique that simultaneously reveals the function of small populations of cells as well as the structure of surrounding brain tissue. These unique properties cause TPCI to be increasingly popular for experimental basic neuroscience. Unfortunately, methodological development for data processing has not kept pace with experimental needs. I address this lack by developing and testing new methodology for several key tasks. Specifically, I address two primary analysis steps which are nearly universally required in early data processing
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Akyuz, Ahmet Oguz. "Optimizing The High Dynamic Range Imaging Pipeline." Doctoral diss., University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4126.

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High dynamic range (HDR) imaging is a rapidly growing field in computer graphics and image processing. It allows capture, storage, processing, and display of photographic information within a scene-referred framework. The HDR imaging pipeline consists of the major steps an HDR image is expected to go through from capture to display. It involves various techniques to create HDR images, pixel encodings and file formats for storage, tone mapping for display on conventional display devices and direct display on HDR capable screens. Each of these stages have important open problems, which need to b
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Gil, Rodríguez Raquel. "Digital camera colour processing pipeline for high dynamic range imaging and colour stabilisation for cinema." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/664378.

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In this thesis we focus on two different image processing challenges: high dynamic range (HDR) image/video generation, and colour matching. In both cases, we redefine these tasks by taking into account the prior knowledge from the different processes the camera performs when capturing the image. High dynamic range techniques have recently become very popular, thanks to the emergence of HDR recording and displaying technology. We propose two different approaches for HDR creation, one for still images, and one for video creation. In case of still images, most of previous methods follow a multiple ex
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Reyes, Gomez Juan Pablo. "Astronomical image processing from large all-sky photometric surveys for the detection and measurement of type Ia supernovae." Thesis, Aix-Marseille, 2019. http://www.theses.fr/2019AIXM0144.

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Cette thèse présente plusieurs contributions au software developé pour le traitement d’images dans le cadre du LSST. Notre objectif est d'utiliser le code et les algorithmes LSST existants, afin de créer un pipeline dédié à la détection des supernovae de type Ia. Pour la détection des supernovae nous utilisons une technique appelée soustraction optimale d'images qui implique la construction de coadditions. Nous étudions aussi le comportement des différents objets dans le temps et construisons des courbes de lumière qui représentent leur cycle de vie en fonction de l'intensité lumineuse de chaq
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Books on the topic "Image Processing Pipelines"

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Jim Blinn's corner: A trip down the graphics pipeline. Morgan Kaufmann Publishers, 1996.

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Sanz, J. L. C. Radon and projection transform-based computer vision: Algorithms, a pipeline architecture, and industrial applications. Springer-Verlag, 1988.

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Hirakawa, Keigo, and Farhan Baqai. Digital Camera Processing Pipeline. Wiley & Sons, Limited, John, 2023.

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Digital Camera Processing Pipeline. Wiley & Sons, Limited, John, 2010.

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Blinn, Jim. Jim Blinn's Corner: A Trip down the Graphics Pipeline. Elsevier Science & Technology Books, 1996.

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Book chapters on the topic "Image Processing Pipelines"

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Bell, Steven, Jing Pu, James Hegarty, and Mark Horowitz. "Image Processing with Stencil Pipelines." In Compiling Algorithms for Heterogeneous Systems. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-01758-2_3.

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Zhang, Qi, Terry M. Peters, and Roy Eagleson. "Medical Image Volumetric Visualization: Algorithms, Pipelines, and Surgical Applications." In Medical Image Processing. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9779-1_13.

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Roch, Peter, Bijan Shahbaz Nejad, Marcus Handte, and Pedro José Marrón. "Systematic Optimization of Image Processing Pipelines Using GPUs." In Advances in Visual Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64559-5_50.

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Estevez-Velarde, Suilan, Yoan Gutiérrez, Andrés Montoyo, and Yudivián Almeida-Cruz. "Optimizing Natural Language Processing Pipelines: Opinion Mining Case Study." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33904-3_15.

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Fleury, Martin, Andy C. Downton, and Adrian F. Clark. "Karhünen-Loève transform: An exercise in simple image-processing parallel pipelines." In Euro-Par'97 Parallel Processing. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0002818.

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Qin, Haina, Longfei Han, Juan Wang, et al. "Attention-Aware Learning for Hyperparameter Prediction in Image Processing Pipelines." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19800-7_16.

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Ragan-Kelley, Jonathan, Andrew Adams, Sylvain Paris, Marc Levoy, Saman Amarasinghe, and Frédo Durand. "Decoupling Algorithms from Schedules for Easy Optimization of Image Processing Pipelines." In Seminal Graphics Papers: Pushing the Boundaries, Volume 2. ACM, 2023. http://dx.doi.org/10.1145/3596711.3596751.

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Kar, Anuradha. "Towards Improving Bio-Image Segmentation Quality Through Ensemble Post-processing of Deep Learning and Classical 3D Segmentation Pipelines." In Practical Applications of Computational Biology and Bioinformatics, 16th International Conference (PACBB 2022). Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17024-9_7.

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Jonker, Petrus Paulus. "Pipelined low level image processing." In Morphological Image Processing: Architecture and VLSI design. Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-2804-3_5.

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Bajcsy, Peter, Joe Chalfoun, and Mylene Simon. "Functionality of Web Image Processing Pipeline." In Web Microanalysis of Big Image Data. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-63360-2_2.

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Conference papers on the topic "Image Processing Pipelines"

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Ikarashi, Yuka, Jonathan Ragan-Kelley, Tsukasa Fukusato, Jun Kato, and Takeo Igarashi. "Guided Optimization for Image Processing Pipelines." In 2021 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). IEEE, 2021. http://dx.doi.org/10.1109/vl/hcc51201.2021.9576341.

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Johnson, G. Allan, Robert J. Anderson, James J. Cook, Christopher Long, and Alexandra Badea. "Image-processing pipelines: applications in magnetic resonance histology." In SPIE Medical Imaging, edited by Martin A. Styner and Elsa D. Angelini. SPIE, 2016. http://dx.doi.org/10.1117/12.2203525.

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Chai, Sek, Kilho Son, and Jesse Hostetler. "Bootstrapping Deep Neural Networks from Approximate Image Processing Pipelines." In 2019 2nd Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications (EMC2). IEEE, 2019. http://dx.doi.org/10.1109/emc249363.2019.00009.

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Belevich, Ilya. "Protocol organizer for automated image processing pipelines on MIB." In European Microscopy Congress 2020. Royal Microscopical Society, 2021. http://dx.doi.org/10.22443/rms.emc2020.1351.

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Hertel, Dirk, Edward Chang, Loren Shih, and Jason Sproul. "Performance evaluation of digital still camera image processing pipelines." In Electronic Imaging 2007. SPIE, 2007. http://dx.doi.org/10.1117/12.705380.

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Chugh, Nitin, Vinay Vasista, Suresh Purini, and Uday Bondhugula. "A DSL Compiler for Accelerating Image Processing Pipelines on FPGAs." In PACT '16: International Conference on Parallel Architectures and Compilation. ACM, 2016. http://dx.doi.org/10.1145/2967938.2967969.

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Garrett, J. L., S. Bakken, E. F. Prentice, et al. "Hyperspectral Image Processing Pipelines on Multiple Platforms for Coordinated Oceanographic Observation." In 2021 11th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2021. http://dx.doi.org/10.1109/whispers52202.2021.9483993.

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Zhang, Qi, Pei-wen Que, and Yi-mei Mao. "Feature Extraction of Ultrasonic Flaw Signals of Pipelines Using Hilbert-Huang Transform." In 2008 Congress on Image and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/cisp.2008.237.

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Yang, Zhigang, Wen Gao, Yan Liu, and Debin Zhao. "Software Pipelines Design for Variable Block-Size Motion Estimation with Large Search Range." In 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4379797.

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Purini, Suresh, Vinamra Benara, Ziaul Choudhury, and Uday Bondhugula. "Bitwidth customization in image processing pipelines using interval analysis and SMT solvers." In CC '20: 29th International Conference on Compiler Construction. ACM, 2020. http://dx.doi.org/10.1145/3377555.3377899.

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Reports on the topic "Image Processing Pipelines"

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Asari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan, and Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Pipeline Research Council International, Inc. (PRCI), 2015. http://dx.doi.org/10.55274/r0010891.

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A novel algorithmic framework for the robust detection and classification of machinery threats and other potentially harmful objects intruding onto a pipeline right-of-way (ROW) is designed from three perspectives: visibility improvement, context-based segmentation, and object recognition/classification. In the first part of the framework, an adaptive image enhancement algorithm is utilized to improve the visibility of aerial imagery to aid in threat detection. In this technique, a nonlinear transfer function is developed to enhance the processing of aerial imagery with extremely non-uniform l
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Mbani, Benson, Timm Schoening, and Jens Greinert. Automated and Integrated Seafloor Classification Workflow (AI-SCW). GEOMAR, 2023. http://dx.doi.org/10.3289/sw_2_2023.

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The Automated and Integrated Seafloor Classification Workflow (AI-SCW) is a semi-automated underwater image processing pipeline that has been customized for use in classifying the seafloor into semantic habitat categories. The current implementation has been tested against a sequence of underwater images collected by the Ocean Floor Observation System (OFOS), in the Clarion-Clipperton Zone of the Pacific Ocean. Despite this, the workflow could also be applied to images acquired by other platforms such as an Autonomous Underwater Vehicle (AUV), or Remotely Operated Vehicle (ROV). The modules in
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Groeneveld, Davis, and Williams. L51974 Automated Detection of Encroachment Events Using Satellite Remote Sensing. Pipeline Research Council International, Inc. (PRCI), 2002. http://dx.doi.org/10.55274/r0011300.

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As an integral part of the ongoing effort to develop an operational capability of remote sensing based pipeline encroachment monitoring, this investigation focused on the development of automated target detection using synthetic aperture radar (RADARSAT) and optical (QUICKBIRD, EROS) satellite imagery. Specifically, the study aimed at meeting the following objectives: To develop automated target detection algorithms for optical and radar imagery that replicate detection rates obtained through visual image interpretation; To investigate the utility of newly available high-resolution optical sat
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Randell. L51857 Evaluation of Digital Image Acquisition and Processing Technologies for Ground Movement Monitoring. Pipeline Research Council International, Inc. (PRCI), 2008. http://dx.doi.org/10.55274/r0011244.

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Ground movement may occur due to landslides, seismic activity, adjacent earth works, thaw settlement of permafrost, frost heave, or a variety of other causes. When soil moves relative to a pipeline, loads are imposed on the pipeline that will tend to stress it. Portions of the pipeline are anchored or loaded by the moving soil mass, while adjacent portions are anchored in the intact soil and tend to restrain the pipeline. These soil movements and restraints set up stresses within the pipeline that, depending upon the magnitude of the stresses and the nature of the pipeline, may cause damage or
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Author, Unknown. DTRS56-02-T-0005 Digital Mapping of Buried Pipelines with a Dual Array System. Pipeline Research Council International, Inc. (PRCI), 2005. http://dx.doi.org/10.55274/r0011943.

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The technical goal of the Dual Array Project was to develop new technology for non-invasive mapping of buried pipelines, down to depths of 10 meters or more, using modern electromagnetic sensors and signal processing. A major proposed innovation in the work was the integration of the sensor arrays and software into a mobile system capable of mapping underground utility networks (and other buried infrastructure) efficiently over large areas. Ultimately, the goal is to have a non-invasive system that can produce an accurate infrastructure map of an entire urban or suburban utility network in dig
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L41038 Digital Image Acquisition and Processing Technologies for Ground Movement Monitoring of Pipelines. Pipeline Research Council International, Inc. (PRCI), 2000. http://dx.doi.org/10.55274/r0011284.

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The objectives of this project were to evaluate and, where appropriate, enhance the ability of satellite-based interferometric synthetic aperture radar (InSAR) and airborne laser range-finding to delineate and monitor slope movements along pipeline right-of-ways. Particular emphasis was placed on operational issues, and especially the problems associated with applying these technologies in areas where natural vegetation precludes a straightforward analysis.
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