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检索条件"任意字段=17th Image Processing: Algorithms and Systems Conference, IPAS 2019"

共 249 条记录，以下是51-60 订阅

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Solving Nonlinear Equations systems with a Two-Phase Root-Finder Based on Niching Differential Evolution 15th

Solving Nonlinear Equations Systems with a Two-Phase Root-Fi...

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15th International conference on Bio-Inspired Computing: theories and Applications, BIC-TA 2020

作者： Duan, Lianlang Xu, Fei Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9789811613531

Solving nonlinear equation systems (NESs) is a challenging problems in numerical computation. Two goals should be considered for solving NESs. One is to locate as many roots as possible and the other is to improve the solving precision. In this work, in order to achieve these two goals, a two-phase niching differential evolution (TPNDE) is proposed. the innovation of TPNDE is mainly reflected in the following three aspects. First, a probabilistic mutation mechanism is designed to increase the diversity of the population. Second, a novel reinitialization procedure is proposed to detect converged individuals and explore more new regions that may contain global optima. third, distribution adjustment local search (DALS) is proposed to deal with the isolated solution and enhance the convergence of the algorithm. To evaluate the performance of TPNDE, we test our TPNDE and 5 state-of-the-art algorithms on 20 NESs with diverse features. the experimental results show that the proposed TPNDE algorithm is better than the other methods. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Nonlinear equations

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Evaluating the effectiveness of image quality metrics in a light field scenario 17

Evaluating the effectiveness of image quality metrics in a l...

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17th image processing: algorithms and systems conference, ipas 2019

作者： Arru, Giuliano Battisti, Federica Carli, Marco Department of Engineering Universitá degli Studi Roma Tre Rome Italy

In this contribution, an objective metric for quality evaluation of light field images is presented. the method is based on the exploitation of the depth information of a scene, that is captured with high accuracy by the light field imaging system. the depth map is estimated both from the original and impaired light field data. then, a similarity measure is applied, and a mapping is performed to link the depth distortion with the perceived quality. Experimental test performed by comparing state-of-art metrics with the proposed one, demonstrate the effectiveness of the proposed metric. © 2019, Society for Imaging Science and Technology.

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image stitching by creating a virtual depth 17

Image stitching by creating a virtual depth

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17th image processing: algorithms and systems conference, ipas 2019

作者： Eid, Ahmed H. Cooper, Brian E. Cholewo, Tomasz J. Lexmark International Inc. LexingtonKY United States

A method for image stitching is presented. the approach focuses on images with parallax (depth variation) to create panoramic views with high fidelity. the approach creates the stitching seam at a virtual depth to convert hard stitching problems to simple ones. the virtual depth is created by applying local distortions to the input images at the stitching seam so that the contents visually appear to be located at the same depth. the presented approach targets a wide variety of applications that require generating high (or super) resolution, wide-view images. these applications include tele-presence (or tele-reality) applications such as shopping, touring, conferencing, planning or architecting, learning, inspection, and surveillance. Our results show that the proposed approach provides promising results compared to commercial products that rely on stitching solutions. © 2019, Society for Imaging Science and Technology.

关键词： Geometrical optics

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Stereo and Mono Depth Estimation Fusion for an Improved and Fault Tolerant 3D Reconstruction

Stereo and Mono Depth Estimation Fusion for an Improved and ...

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IEEE International conference on Intelligent Computer Communication and processing (ICCP)

作者： Mircea Paul Muresan Marchis Raul Sergiu Nedevschi Radu Danescu Technical University of Cluj-Napoca Cluj-Napoca Romania

ISBN: (纸本)9781665409773

Depth estimation approaches are crucial for environment perception in applications like autonomous driving or driving assistance systems. Solutions using cameras have always been preferred to other depth estimation methods, due to low sensor prices and their ability to extract rich semantic information from the scene. Monocular depth estimation algorithms using CNNs may fail to reconstruct due to unknown geometric properties of certain objects or scenes, which may not be present during the training stage. Furthermore, stereo reconstruction methods, may also fail to reconstruct some regions for various other reasons, like repetitive surfaces, untextured areas or solar flares to name a few. To mitigate the reconstruction issues that may appear, in this paper we propose two refinement approaches that eliminate regions which are not correctly reconstructed. Moreover, we propose an original architecture for combining the mono and stereo results in order to obtain improved disparity maps. the proposed solution is designed to be fault tolerant such that if an image is not correctly acquired or is corrupted, the system is still able to reconstruct the environment. the proposed approach has been tested on the KITTI dataset in order to illustrate its performance.

关键词： Training Fault tolerance Surface reconstruction three-dimensional displays Fault tolerant systems Semantics Estimation

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Data engineering for the automation of non-contact foliar diagnostics of plants based on the HSL model of color formation

Data engineering for the automation of non-contact foliar di...

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International Computer Sciences and Information Technologies (CSIT)

作者： Natalia A. Pasichnyk Oleksiy A. Opryshko Dmytro S. Komarchuk Nadiia A. Yasinska Ruslan S. Rakhmedov Nikolay A. Kiktev Department of Agricultural Chemistry and Quality of Plant Products National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine R&D Department Fichessoft LLC 2105 Vista Oeste NW Albuquerque NM USA Presidium of the National Academy of Agrarian Sciences of Ukraine Kyiv Ukraine Software Department Stripe Inc 354 Oyster Point Blvd South San Francisco CA USA

ISBN: (纸本)9798350334326

the work is devoted to implementing traditional technologies of visual monitoring of plants for precision agriculture technologies, namely data engineering for the improvement of remote monitoring of marker vegetation indices with the help of UAVs. Classic vegetation indices such as NDVI that used to solve a limited range of problems and them mainly used to adjust the number of nitrogen fertilizers during differentiated treatment of field areas. Such indices are poorly adapted to identify the causes of stress. For stresses of a technical nature, in particular, on winter rapeseed crops, marker indices are used, which, with the traditional model of color formation, are difficult to adjust to identify anomalous coloration of affected plants. In addition, the accuracy of classical indices for the additive color formation model is affected by changes in lighting, increasing the accuracy of anomaly identification requires additional adjustment based on the state of the atmosphere at the time of image acquisition. the purpose of the work is the formation of a new approach to the automation of visual diagnostics of plants, which is based on the adaptation of machine vision technologies to the existing technologies of noncontact expert assessment of plants. A hypothesis was put forward about the possibility of creating vegetation indices based on an alternative model of HSL coloration, which would be more resistant to changes in illumination. the research was carried out on winter wheat crops in April-May 2021, archival images of winter rapeseed crops affected by technological stress taken in 2019 were also used. Photography was carried out using a Phantom 2 UAV in the visible range of the spectrum. Data processing was performed in the MathCad environment. the research was conducted on the resistance to changes in lighting during hardware adjustment of the exposure of images, as well as the features of object identification, namely, healthy and affected leaves and soil in th

关键词： Resistance Visualization image color analysis Atmospheric modeling Stability criteria Vegetation mapping Lighting

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Patch-based image despeckling using low-rank hankel matrix approach with speckle level estimation 17

Patch-based image despeckling using low-rank hankel matrix a...

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17th image processing: algorithms and systems conference, ipas 2019

作者： Kim, Hansol Oh, Paul Lee, Sangyoon Kang, Moon G.I. School of Electrical and Electronic Engineering Yonsei University 50 Yonsei-ro Seodaemun-gu Seoul03722 Korea Republic of

In this study, we propose an image despeckling method based on low-rank Hankel matrix approach and speckle level estimation. Annihilating filter-based low-rank Hankel matrix, so called ALOHA approach is very useful to various areas, such as image inpainting and impulse noise reduction. the proposed method utilizes this approach because it provides high performance in completing irregularly subsampled images. Speckled image are subsampled using patch-based speckle level estimator which selects pixels with low speckle level and abandon the others. the subsampled image is reconstructed using low-rank structured matrix completion. Our experimental results demonstrate that precisely estimated speckle level improves despeckling performance significantly. the accuracy of the proposed speckle estimator validates better despeckling performance of the proposed method compared with conventional despeckling methods. © 2019, Society for Imaging Science and Technology.

关键词： Speckle

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Gradient management and algebraic reconstruction for single image super resolution 17

Gradient management and algebraic reconstruction for single ...

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17th image processing: algorithms and systems conference, ipas 2019

作者： Delfin, Leandro Morera Elias, Raul Pinto de Jesús Ochoa Domínguez, Humberto Center of Investigation and Technological Development CENIDET Morelos Mexico Universidad Autónoma de Ciudad Juárez UACJ Chihuahua Mexico

In this paper, a single image multi-scale super-resolution technique is proposed. the concept under study is the learning procedure between steps of amplification in order to predict the next high scale of resolution. the method integrates two different approaches for the prediction of a high resolution multi-scale scheme, a pure interpolation and a gradient regularization. In the first step a pure interpolation is carried out. It is used a prediction scheme with algebraic reconstruction through different scales to produce the high resolution output. In the last step, the residual blur is reduced by a gradient auto-regularization method. the gradients are adapted by using a weight in a neighbour. Precision of method can be controlled by the parameters of an algebraic reconstruction technique (ART). the proposed model avoids the fast decrease of the output resolution as the amplification factor increases. the proposed system was tested with a dictionary. Results show that the output image quality is improved despite of the increment of the scale factor. © 2019, Society for Imaging Science and Technology.

关键词： Interpolation

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Microscope image matching in scope of multi-resolution observation system 17

Microscope image matching in scope of multi-resolution obser...

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17th image processing: algorithms and systems conference, ipas 2019

作者： Putranto, Evan H.E. Usuki, Shin Miura, Kenjiro T. Graduate School of Engineering Shizuoka University Japan Research Institute of Electronics Shizuoka University Japan

Multi-resolution image processing are part of this concept that has a purpose to extracting the detail information of the multi-scale input image. However, in general, to process a multi-scale image there are issue that need to be solved, for an instance color difference, image matching failure, and lack of data which can be observe in a same time. In the same way, observation are work where object of interest are being analyze and being perceive. Observing a multi-resolution image with a lot of object interest would be a daunting task to do. there have been many attempts to match and stitch two or more images into one but still has a chance to get failure. In this article, the author propose a multi-resolution image observation system which are focus on three improvement field successfulness rating of image matching, utilize a classification algorithm to help perceiving object interest and user-friendly interface viewer. On pre-processing, this system take a four type magnification level of image;10 ×, 20 ×, 50 ×, 150 ×. By investigating image matching parameter to stitching group of images, handling false positive of feature point occurred, and then finally arrange and show group of synthesized images inside web application, we believe user can observe microscopic image in a cushioned way. © 2019, Society for Imaging Science and Technology.

关键词： image matching

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Measuring camera shannon information capacity with a siemens star image 17

Measuring camera shannon information capacity with a siemens...

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17th image Quality and System Performance conference, IQSP 2020

作者： Koren, Norman L. Imatest LLC BoulderCO United States

Shannon information capacity, which can be expressed as bits per pixel or megabits per image, is an excellent figure of merit for predicting camera performance for a variety of machine vision applications, including medical and automotive imaging systems. Its strength is that is combines the effects of sharpness (MTF) and noise, but it has not been widely adopted because it has been difficult to measure and has never been standardized. We have developed a method for conveniently measuring information capacity from images of the familiar sinusoidal Siemens Star chart. the key is that noise is measured in the presence of the image signal, rather than in a separate location where image processing may be different-a commonplace occurrence with bilateral filters. the method also enables measurement of SNRI, which is a key performance metric for object detection. Information capacity is strongly affected by sensor noise, lens quality, ISO speed (Exposure Index), and the demosaicing algorithm, which affects aliasing. Information capacity of in-camera JPEG images differs from corresponding TIFF images from raw files because of different demosaicing algorithms and nonuniform sharpening and noise reduction. © 2020 Society for Imaging Science and Technology.

关键词： Object detection

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Multi-frame super-resolution utilizing spatially adaptive regularization for ToF camera 17

Multi-frame super-resolution utilizing spatially adaptive re...

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17th image processing: algorithms and systems conference, ipas 2019

作者： Lee, Haegeun Kim, Jonghyun Han, Jaeduk Kang, Moon G.I. School of Electrical and Electronic Engineering Yonsei University 50 Yonsei-ro Seodaemun-gu Seoul03722 Korea Republic of

Recently, 3D time-of-flight cameras have been developed. the development enables utilization of depth images in various fields. However, acquired depth images are corrupted by noise during the image acquisition process and have relatively lower resolution than RGB images due to the limitation of ToF cameras. In this paper, a multi-frame super-resolution reconstruction algorithm is proposed for ToF depth images to overcome such limits. the purpose of the multi-frame super-resolution reconstruction is to reconstruct a high-resolution image from observed multiple low-resolution images through the sequential process of subpixel estimation and restoration. A conventional regularized super-resolution reconstruction algorithm which takes Tikhonov regularization has a major drawback of over-smoothing around edges. To overcome the disadvantage, the spatially adaptive regularization is suggested for preservation of edges. Experimental results show that the image reconstructed by the proposed super-resolution reconstruction algorithm contains significantly higher resolution with less amount of noise and sharper edges than the observed data. © 2019, Society for Imaging Science and Technology.

关键词： image acquisition

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