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imaging processing: algorithms and systems iii

The proceedings contain 59 papers from the Conference of SPIE - Image processing: algorithms and systems iii. The topics discussed include: the fast parametric slantlet transform with applications;parameterized reversible integer discrete cosine transform;variations of matched filtering for reduced noise amplification;pupil detection in photo ID;template gradient matching in spherical images;and imaging-based dust sensors;equipment and methods.

关键词： Image processing

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Deep learning for plant stress detection: A comprehensive review of technologies, challenges, and future directions

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2025年 229卷

作者： Paul, Nijhum Sunil, G. C. Horvath, David Sun, Xin North Dakota State Univ Dept Agr & Biosyst Engn Fargo ND 58108 USA North Dakota State Univ Genom Phen & Bioinformat Program Fargo ND 58108 USA USDA ARS ETSARC Weed & insect Biol unit Fargo ND 58102 USA

Deep learning (DL)-based systems have emerged as powerful methods for the diagnosis and treatment of plant stress, offering high accuracy and efficiency in analyzing imagery data. This review paper aims to present a thorough overview of the state-of-the-art DL technologies for plant stress detection. For this purpose, a systematic literature review was conducted to identify relevant articles for highlighting the technologies and approaches currently employed in the development of a DL-based plant stress detection system, specifically the advancement of image-based data collection systems, image preprocessing techniques, and deep learning algorithms and their applications in plant stress classification, disease detection, and segmentation tasks. Additionally, this review emphasizes the challenges and future directions in collecting and preprocessing image data, model development, and deployment in real-world agricultural settings. Some of the key findings from this review paper are: Training data: (i) Most plant stress detection models have been trained on Red Green Blue (RGB) images;(ii) Data augmentation can increase both the quantity and variation of training data;(iii) Handling multimodal inputs (e. g., image, temperature, humidity) allows the model to leverage information from diverse sources, which can improve prediction accuracy;Model Design and Efficiency: (i) Self-supervised learning (SSL) and Few-shot learning (FSL)-based methods may be better than transfer learning (TL)-based models for classifying plant stress when the number of labeled training images are scarce;(ii) Custom designed DL architectures for a specific stress and plant type can have better performance than the state-of-the-art DL architectures in terms of efficiency, overfitting, and accuracy;(iii) The multi-task learning DL structure reuses most of the network architecture while performing multiple tasks (e.g., estimate stress type and severity) simultaneously, which makes the learning much

关键词： Plant stress Computer vision Deep learning Image processing imaging sensor Precision agriculture

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Toward a super imaging system [Invited]

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APPLIED OPTICS 2013年第4期52卷 561-566页

作者： Mendlovic, David Tel Aviv Univ Fac Engn IL-69978 Tel Aviv Israel

This paper deals with the fast-developing area of computational photography where a combination of imaging techniques and efficient image processing algorithms is done to generate a super imaging system. In recent years, three main implementations of the computational photography philosophy were intensively investigated and demonstrated: (i) multiple aperture, (ii) light field photography, and (iii) multiexposure. The paper provides a mini-review of these three approaches and shows ways to improve and combine them toward a super imaging system. As a conclusion, the paper provides preliminary guidelines for fusing the three approaches into one integrated super imaging system with optimized performance. (C) 2013 Optical Society of America

关键词： Image processing Image processing algorithms Image quality imaging systems imaging techniques Optical imaging

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Review Paper: An outlook on the future of seismic imaging, Part iii: Joint Migration Inversion

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GEOPHYSICAL PROSPECTING 2014年第5期62卷 950-971页

作者： Berkhout, A. J. (Guus) Delft Univ Technol CiTG NL-2628 CN Delft Netherlands

The next generation seismic imaging algorithms will consider multiple scattering as indispensable information, referred to as Full Wavefield Migration. In addition, these algorithms will also include autonomous velocity updating in the migration process, referred to as Joint Migration Inversion. Full wavefield migration and joint migration inversion address the industrial needs of improving images of very complex reservoirs as well as the industry ambition of producing these images in a more automatic manner ('automation in seismic processing'). In this vision paper on seismic imaging, full wavefield migration and joint migration inversion are formulated in terms of a closed-loop, estimation algorithm that can be physically explained by an iterative double focusing process (full wavefield Common-Focus-Point technology). A critical module in this formulation is forward modelling, allowing feedback from migrated output to unmigrated input ('closing the loop'). For this purpose a full wavefield modelling module has been developed that utilizes an operator description of complex geology. Full wavefield modelling module is pre-eminently suited to function in the feedback path of a closed-loop migration algorithm. 'The Future of Seismic imaging' is presented as a coherent trilogy, proposing in three consecutive parts the migration framework of the future. In part I it was shown that the proposed full wavefield modelling module algorithm differs fundamentally from finite difference modelling, as velocities and densities need not be provided. Instead, full wavefield modelling module uses an operator description of the subsurface. In Part II it was shown how the theory of Primary Wavefield Migration can be extended to Full Wavefield Migration by correcting for elastic transmission effects and by utilizing multiple scattering. In Part iii it is shown how the full wavefield migration technology can be extended to Joint Migration Inversion, allowing full wavefield migration of

关键词： imaging systems in seismology STRATIGRAPHIC geology FEEDBACK control systems ITERATIVE methods (Mathematics) NUMERICAL analysis

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AUTOMATIC CORRELATION OF NON-COMPATIBLE imaging systems.

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1979年 230-233页

作者： Boland iii, J.S. Peters, E.G. Pinson, Lewis J. Malcolm, W.W.

This paper considers the difficult problem of target hand-off between two imaging devices sensitive in different frequency spectra. The types of imaging systems considered are a high resolution day TV pointing and tracking system for target acquisition and a low resolution Infra-Red imaging Seeker for the missile. Automatic correlation of two digital arrays obtained from non-compatible imaging systems is considered. Several preprocessing algorithms are presented which transform the input video signals to a compatible format for input to a binary correlation system. The results of implementing the preprocessing algorithms in a correlation system simulation are given and explained. A preprocessing algorithm using edge detection is chosen and the advantages and disadvantages are listed.

关键词： IMAGE processing

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A focus of attention mechanism for gaze control within a framework for intelligent image analysis tools

A focus of attention mechanism for gaze control within a fra...

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Conference on Image processing - algorithms and systems iii

作者： Rodrigo, R Ranaweera, K Samarabandu, J Univ Western Ontario Dept Elect & Comp Engn London ON N6A 5B9 Canada

ISBN: (纸本)0819452017

Focus of attention is often attributed to biological vision system where the entire field of view is first monitored and then the attention is,focused to the object of interest. We propose using a similar approach for object recognition in a color image sequence. The intention is to locate an object based on a prior motive, concentrate on the detected object so that the imaging device can be guided toward it. We use the abilities of the intelligent image analysis framework developed in our laboratory to generate an algorithm dynamically to detect the particular type of object based on the user's object description. The proposed method uses color clustering along with segmentation. The segmented image with labeled regions is used to calculate the shape descriptor parameters. These and the color information are matched with the input description. Gaze is then controlled by, issuing camera movement commands as appropriate. We present some preliminary results that demonstrate the success of this approach.

关键词： Image segmentation Image processing Image analysis imaging devices Cameras Algorithm development Image processing algorithms and systems Control systems imaging systems Shape analysis

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Preliminary investigation of the frequency response and distortion properties of nonlinear image processing algorithms

Preliminary investigation of the frequency response and dist...

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Conference on Medical imaging - Physics of Medical imaging

作者： Wells, Jered R. Dobbins, James T., iii Duke Univ Med Ctr Carl E Ravin Adv Imaging Labs Durham NC 27705 USA

ISBN: (纸本)9780819494429

Assessment of the resolution properties of nonlinear imaging systems is a useful but challenging task. While the modulation transfer function (MTF) fully describes contrast resolution as a function of spatial frequency for linear systems, an equivalent metric does not exist for systems with significant nonlinearity. Therefore, this preliminary investigation attempts to classify and quantify the amount of scaling and distortion imposed on a given image signal as the result of a nonlinear process (nonlinear image processing algorithm). As a proof-of-concept, a median filter is assessed in terms of its principle frequency response (PFR) and distortion response (DR) functions. These metrics are derived in frequency space using a sinusoidal basis function, and it is shown that, for a narrow-band sinusoidal input signal, the scaling and distortion properties of the nonlinear filter are described exactly by PFR and DR, respectively. The use of matched sinusoidal basis and input functions accurately reveals the frequency response to long linear structures of different scale. However, when more complex (multi-band) input signals are considered, PFR and DR fail to adequately characterize the frequency response due to nonlinear interaction effects between different frequency components during processing. Overall, the results reveal the context-dependent nature of nonlinear image processing algorithm performance, and they emphasize the importance of the basis function choice in algorithm assessment. In the future, more complex forms of nonlinear systems analysis may be necessary to fully characterize the frequency response properties of nonlinear algorithms in a context-dependent manner

关键词： nonlinear algorithms frequency response image processing metrology

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High dynamic range imaging for digital still camera: an overview

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JOURNAL OF ELECTRONIC imaging 2003年第3期12卷 459-469页

作者： Battiato, S Castorina, A Mancuso, M STMicroelect Adv Syst Technol Catania Lab Imaging & Multimedia Mobile Grp Catania Italy

We present a collection of methods and algorithms able to deal with high dynamic ranges of real pictures acquired by digital engines e.g., charge-coupled device (CCD/CMOS) cameras. An accurate image acquisition can be challenging under difficult light conditions. A few techniques that overcome dynamic range limitations problems are reported. The presented methods allow the recovery of the original radiance values of the final 8-bit-depth image starting from differently exposed pictures. This allows the capture of both low- and high-light details by merging the various pictures into a single map, thus providing a more faithful description of what the real world scene was. However, in order to be viewed on a common computer monitor, the map needs to be compressed and requantized while preserving the visibility of details. The main problem comes from the fact that the contrast of the radiance values is usually far greater than that of the display device. Various related techniques are reviewed and discussed. (C) 2003 SPIE and IST.

关键词： Image restoration Cameras Image sensors Sensors High dynamic range imaging Image processing CMOS sensors Digital cameras Image compression imaging systems

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Microwave Photonic Synthetic Aperture Radar: systems, experiments, and imaging processing

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IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE 2024年 2-16页

作者： Chen, Jianlai Xiong, Rongqi Yu, Hanwen Xu, Gang Li, Ruoming Xing, Mengdao Cent South Univ Changsha 410083 Peoples R China Univ Houston Natl Ctr Airborne Laser Mapping Dept Civil & Environm Engn Houston TX USA Univ Elect Sci & Technol China Sch Resources & Environm Chengdu 611731 Peoples R China Xidian Univ Acad Adv Interdisciplinary Res Xian Peoples R China Univ Naples Federico II Dept Engn Naples Italy Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore Southeast Univ Sch Informat Sci & Engn State Key Lab Millimeter Waves Nanjing 210096 Peoples R China Nanjing Univ Coll Engn & Appl Sci Nanjing Peoples R China Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China Xidian Univ Acad Adv Interdisciplinary Res Dept Xian Peoples R China

With the development of synthetic aperture radar (SAR) technology, the resolution of SAR images has been improved from tens of meters to centimeters (currently the highest). However, increasing image resolution from centimeters to millimeters will pose a significant challenge to the hardware and signal processing algorithms of traditional radar systems. Fortunately, the emergence of microwave photonic technology assisted SAR systems in recent years is expected to solve this bottleneck. The system is theoretically capable of achieving a signal bandwidth of 10 GHz or even tens of GHz. However, the rapid increase in resolution will also bring new problems and challenges. For example, i) How to address the adverse effects of system instability under ultra-large signal bandwidth;ii) How to improve the imaging efficiency in the case of a sharp increase in data volume;iii) How to overcome the more complex signal characteristics faced by ultra-high-resolution imaging. Although microwave photonic SAR systems and data processing techniques are not yet sufficiently developed, they have great potential and will be a very hot and cutting-edge research field at present and in the future. In this paper, we will make a comprehensive review, summary, and prospect of the related research on microwave photonic SAR from three aspects of systems, experiments, and imaging processing. The purpose of this study is to provide some guiding suggestions and references for relevant researchers to promote the further development of microwave photonic SAR technology.

关键词： Image enhancement

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A knowledge capturing approach for a cooperative intelligent image analysis system

A knowledge capturing approach for a cooperative intelligent...

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Conference on Image processing - algorithms and systems iii

作者： Ranaweera, KP Samarabandu, J Univ Western Ontario Dept Elect & Comp Engn London ON N6A 5B9 Canada

ISBN: (纸本)0819452017

We present a generalized approach to dynamically incorporate high level knowledge into a cooperative intelligent image analysis framework. We developed this framework in our laboratory to provide a uniform interface to develop intelligent image analysis tools as well as to provide infrastructure facilities required by these tools in order to work cooperatively for accomplishing complex image analysis task goals. This framework is able to automatically generate processing plans which accomplish user defined image analysis task goals. The approach that we propose in this paper provides a flexible interface to incorporate high level knowledge in image processing tools. We provide two ways to develop this knowledge: 1) by taking a feedback from an image processing expert about a processing plan generated by the system;and 2) by accepting a processing plan which accomplishes a particular task from an expert user. and then extracting the high level knowledge encapsulated in this plan. The generalized nature of our approach allows each individual tool to use machine learning algorithms of its own interest in improving the knowledge-base. Preliminary results that we obtained from this work demonstrates the success of our approach.

关键词： Image processing Image analysis Intelligence systems Human-machine interfaces Image segmentation Sensors Digital filtering Gaussian filters Image processing algorithms and systems Machine learning

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