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A problem of emphasizing features of a surface roughness by means the Discrete Wavelet Transform

JOURNAL OF MATERIALS PROCESSING TECHNOLOGY 2005年 164卷 1410-1415页

作者： Niola, v Nasti, G Quaremba, G Univ Naples Federico II Dept Mech Engn Energet Naples Italy

When we are interested to the detection of the roughness features by means of the 3D reconstruction, based on photometric stereo techniques, an important problem is the elimination of the brightness variation due to different light conditions which can alter the response. This paper will concentrate on presenting results of a new method for eliminating this problem. Every pixel of a picture gives only one number: the brightness of the corresponding point on the object, whereas the surface orientation is described by a normal vector that has two degrees of freedom. The level of brightness depends on many factors as well as the homogeneity of reflection properties of the material or its physical continuity and the surface smoothness or roughness. In this work we will show how the application of the Discrete Wavelet Transform (DWT) to the processing of some images, captured on different light conditions, permits to solve the problem of emphasizing roughness features of a metallic surface. Wavelet transforms can model irregular data patterns such as sharp changes, better than the Fourier transforms and standard statistical procedures (e.g., parametric and non-parametric regressions) and provide a multiresolution approximation to the data. Here we propose, also, a non-parametric method, based on the wavelet theory, for the estimation of the threshold level of a gray levels distribution, obtained from the intensity image matrix. (c) 2005 Elsevier B.v. All rights reserved.

关键词： image processing surface roughness wavelet transform optimum threshold

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Garment motion capture using color-coded patterns

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COMPUTER GRAPHICS FORUM 2005年第3期24卷 439-447页

作者： Scholz, v Stich, T Keckeisen, M Wacker, M Magnor, M MPI Informat Saarbrucken Germany Univ Tubingen GRIS WSI D-72074 Tubingen Germany

In this paper we present an image-based algorithm for surface reconstruction of moving garment from multiple calibrated video cameras. Using a color-coded cloth texture, we reliably match circular features between different camera views. As surface model we use air a priori known triangle mesh. By identifying the mesh vertices with texture elements we obtain a consistent parameterization of the surface over time without further processing. Missing data points resulting from self-shadowing are plausibly interpolated by minimizing a thin-plate functional. The deforming geometry can be used for different graphics applications, e.g. for realistic retexturing. We show results for real garments demonstrating the accuracy of the recovered flexible shape.

关键词： Computer algorithms image processing Computer graphics Surfaces (Geometry) Camcorders

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Global optimization for shape fitting

Global optimization for shape fitting

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IEEE conference on Computer vision and Pattern Recognition

作者： Lempitsky, victor Boykov, Yuri Moscow MV Lomonosov State Univ Dept Math & Mech Moscow Russia Univ Western Ontario Dept Comp Sci London ON N6A 3K7 Canada

ISBN: (纸本)9781424411795

We propose a global optimization framework for 3D shape reconstruction from sparse noisy 3D measurements frequently encountered in range scanning, sparse feature-based stereo, and shape-from-X. In contrast to earlier local or banded optimization methods for shape fitting, we compute global optimum in the whole volume removing dependence on initial guess and sensitivity to numerous local minima. Our global method is based on two main ideas. First, we suggest a new regularization functional with a data alignment term that maximizes the number of (weakly-oriented) data points contained by a surface while allowing for some measurement errors. Second, we propose a touch-expand algorithm for finding a minimum cut on a huge 3D grid using an automatically adjusted band This overcomes prohibitively high memory cost of graph cuts when computing globally optimal surfaces at high-resolution. Our results for sparse or incomplete 3D data from laser scanning and passive multi-view stereo are robust to noise, outliers, missing parts, and varying sampling density.

关键词： image reconstruction

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Wiener Altering of aliased imagery

Wiener Altering of aliased imagery

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image reconstruction from incomplete data v

作者： Thurman, Samuel T. Fienup, James R. Institute of Optics University of Rochester Rochester NY 14627 United States

ISBN: (纸本)9780819472960

We analyze a Fourier-domain Wiener filter for the reconstruction of aliased imagery. The filter is designed to minimize the expected mean square error for the unaliased portion of the object Fourier transform. This analysis yields a net system transfer function, which characterizes the combined effects of the imaging system, sampling, and the reconstruction process, that is valid at both aliased and unaliased spatial frequencies. This transfer function provides insight into how aliasing artifacts are modified by the reconstruction process. Additionally, the net transfer function is useful for characterizing the combined performance of the imaging system and post processing. For example, the net system transfer function can be used to calculate the edge response for reconstructed imagery even in the presence of aliasing. Examples are used to illustrate these aspects of using the Wiener filter with aliased imagery.

关键词： image reconstruction

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Patient evaluation of Breast Shape-corrected Tomosynthesis reconstruction

Patient evaluation of Breast Shape-corrected Tomosynthesis R...

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conference on Medical Imaging - Physics of Medical Imaging

作者： Michielsen, Koen Rangelova, Tsvetanka Sechopoulos, Ioannis Radboudumc Dept Radiol & Nucl Med Nijmegen Netherlands Dutch Reference Ctr Screening LRCB Nijmegen Netherlands

ISBN: (纸本)9781510625440

Iterative reconstruction is a good match with the sparsely sampled limited angle data generated by breast tomosynthesis systems. However, it suffers from a specific artifact near the breast edge where it overestimates the x-ray path length, resulting in a considerable underestimation of the reconstructed linear attenuation coefficients. In this work, we present the application of a method that uses the measured 3D breast shape to reduce these artifacts in patient data, by including this information as an additional constraint in the image reconstruction process. A series of 50 patients undergoing breast tomosynthesis were additionally imaged with a pair of structured light cameras placed left and right of the mammography unit. These 3D surfaces were then aligned with the help of the backprojected breast outline from the x-ray data to form a single contour following the true breast shape. This was then further processed to generate a binary 3D mask set to 1 inside and to 0 outside the breast, and used as constraint in the reconstruction. Due to incomplete coverage and image artifacts, this mask was created successfully for only 19 out of 50 cases. reconstructions were created with and without this constraint, and comparing attenuation profiles found that the artifact was almost completely corrected, bringing the reconstructed attenuation near the breast edge to the same level as the central region. Further visual inspection does show that higher quality optical 3D measurements and more precise alignment between optical and x-ray data are needed to avoid introducing new artifacts in the reconstruction.

关键词： Breast Signal attenuation Cameras X-rays data acquisition reconstruction algorithms 3D acquisition Digital breast tomosynthesis Structured light

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Time Dependent image Generation of Plants from incomplete Sequences with CNN-Transformer 44th

Time Dependent Image Generation of Plants from Incomplete Se...

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44th DAGM German conference on Pattern Recognition (DAGM GCPR)

作者： Drees, Lukas Weber, Immanuel Russwurm, Marc Roscher, Ribana Tech Univ Munich Data Sci Earth Observat Munich Germany Univ Bonn Remote Sensing IGG Bonn Germany AB EX PLEdoc Essen Germany Ecole Polytech Fed Lausanne EPFL ECEO Lab Lausanne Switzerland

ISBN: (纸本)9783031167881;9783031167874

data imputation of incomplete image sequences is an essential prerequisite for analyzing and monitoring all development stages of plants in precision agriculture. For this purpose, we propose a conditional Wasserstein generative adversarial network TransGrow that combines convolutions for spatial modeling and a transformer for temporal modeling, enabling time-dependent image generation of above-ground plant phenotypes. Thereby, we achieve the following advantages over comparable data imputation approaches: (1) The model is conditioned by an incomplete image sequence of arbitrary length, the input time points, and the requested output time point, allowing multiple growth stages to be generated in a targeted manner;(2) By considering a stochastic component and generating a distribution for each point in time, the uncertainty in plant growth is considered and can be visualized;(3) Besides interpolation, also test-extrapolation can be performed to generate future plant growth stages. Experiments based on two datasets of different complexity levels are presented: Laboratory single plant sequences with Arabidopsis thaliana and agricultural drone image sequences showing crop mixtures. When comparing TransGrow to interpolation in image space, variational, and adversarial autoencoder, it demonstrates significant improvements in image quality, measured by multi-scale structural similarity, peak signal-to-noise ratio, and Frechet inception distance. To our knowledge, TransGrow is the first approach for time- and image-dependent, high-quality generation of plant images based on incomplete sequences.

关键词： data imputation Transformer Positional encoding image time series Conditional GAN image generation Plant growth modeling

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Performance Evaluation of reconstruction with Fan-Beam Algorithm with no Backprojection Weight in Truncated Projection Completion using Linear Prediction

Performance Evaluation of Reconstruction with Fan-Beam Algor...

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IEEE Region 10 conference on TENCON

作者： Sumith, K. Narasimhadhan, A. v. Rajgopal, Kasi Indian Inst Sci Dept Elect Engg Bangalore 560012 Karnataka India

ISBN: (纸本)9781457702556

The work presented in this paper examines the performance of reconstruction from truncated projections using linear prediction for projection completion and recently proposed fan beam algorithm having no backprojection weight. The truncation in the tomographic projections can occur due to compact nature of the detector, outsized imaging object and region of interest (ROI) reconstruction applications. The reconstruction of the object function from truncated projections suffers from undesirable truncation artifacts and incorrect reconstructed density values. In this work, the truncated projection data is estimated by using the linear projection technique. The object is then reconstructed from the completed projections by using Hilbert filter based fan-beam algorithm with no backprojection weight. The resulting reconstruction improves the image quality in terms of noise performance characteristics. Simulation results are presented to show the improvements in image quality and compared with the reconstruction obtained using ramp filtered fan-beam algorithm.

关键词： Fan-beam algorithm truncation Linear prediction

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Clouds removal from remotely sensed images by using a bandelet-based reconstruction technique

Clouds removal from remotely sensed images by using a bandel...

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conference on Wavelet Applications in Industrial Processing v

作者： Maalouf, Aldo Carre, Philippe Augereau, Bertrand Fernandez-Maloigne, Christine Univ Politiers Signal Image Communicat Lab F-86962 Futuroscope France

ISBN: (纸本)9780819469236

The recurrent presence of clouds and clouds shadows in aerial or remotely sensed images is an awkward problem that severely limits the regular exploitations capability of these images. Removing cloud-contaminated portions of the image and then filling in the missing data represent an important photo editing cumbersome task. The intent of this work is to propose a technique for the reconstruction of areas obscured by clouds in a remotely sensed image. To this end, a new efficient reconstruction technique for missing data synthesis is presented. This technique is based on the Bandelet transform and the multiscale geometrical grouping. It consists of two steps. In the first step, the curves of geometric flow of different zones of the image are determined by using the Bandelet transform with multiscale grouping. This step allows a better representation of the multiscale geometry of the image's structures. Having well represented this geometry, the information inside the cloud-contaminated zone is synthesized by propagating the geometrical flow curves inside that zone. This step is accomplished by minimizing, a functional whose role is to reconstruct the missing or cloud contaminated zone independently of the size and topology of the reconstruction or inpainting domain. Thus, the flow lines are well tied inside the cloud-contaminated zone. The proposed technique is illustrated with some examples on processing multispectral aerial images. The obtained results are compared with those obtained by other clouds removal techniques.

关键词： Clouds Wavelets image classification image processing reconstruction algorithms Wavelet transforms image segmentation Lithium Remote sensing Multispectral imaging

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Influence of TOF information in OpenPET image reconstruction

Influence of TOF information in OpenPET image reconstruction

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IEEE Nuclear Science Symposium conference 2009

作者： Yamaya, Taiga Yoshida, Eiji Nishikido, Fumihiko Inadama, Naoko Shibuya, Kengo Murayarna, Hideo Natl Inst Radiol Sci Mol Imaging Ctr Chiba Japan Univ Tokyo Grad Sch Arts & Sci Tokyo Japan

ISBN: (纸本)9781424439614

We have proposed an "OpenPET" geometry, which consists of two axially separated detector rings. The central point of the field of view, where the highest sensitivity is obtained, is opened. The OpenPET mainly has three applications, namely, simultaneous PET/CT, extension of the axial FOv, and in-beam PET. In our previous report, we showed that axial spatial resolution, which is degraded with the extended gap due to the parallax error, can be recovered by use of depth-of-interaction (DOI) detectors. On the other hand, image reconstruction of the OpenPET is an incomplete problem because projection data do not satisfy Orlov's condition. Low-frequency components are missing in oblique LORs, i.e., LORs with large ring differences. The gap would suffer from loss of low-frequency components because the gap, where direct LORs (i.e., LORs in the same ring) do not exist, is imaged only from the oblique LORs. In this paper, we focused on time-of-flight (TOF) information, which is expected to compensate for the loss of low-frequency components in the gap. We investigated influence of TOF information in the OpenPET image reconstruction through numerical simulations. Simulated OpenPET scanner had dual detector rings (827.0 mm in diameter and axial length of 153.6 mm each) separated by a gap of 153.6 mm. We supposed that the detectors had a DOI capability of 8 layers and had a TOF capability of 400 ps FWHM resolution. For the non-TOF case, hot-spot objects, which are commonly seen in cancer diagnosis with use of FDG, were imaged without any artifacts, but objects containing more low-frequency components suffered from strong distortion. However, these artifacts were effectively reduced by using TOF information. These results showed that TOF information can compensate for low-frequency components missing in the gap.

关键词： image reconstruction

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Fusion of 3D line features and 2D image line features for building roof reconstruction

Fusion of 3D line features and 2D image line features for bu...

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28th Asian conference on Remote Sensing 2007, ACRS 2007

作者： Jaw, Jen-Jer Cheng, Chieh-Chung Department of Civil Engineering National Taiwan University No. 1 Roosevelt Road Taipei 10617 Taiwan

ISBN: (纸本)9781615673650

The objective of this study is to present an efficient algorithm of building roof reconstruction by fusing 3D line features and 2D image line features through CSR (Construct-Shape-Refine) procedures. The proposed algorithm starts by inputting 3D line features and performs the following geometric inferences: (1) constructing the topological relationship of 3D line features that belong to the same building;(2) shaping the building roof by means of adjustments, compensating missing parts, if any, and reporting whether or not the investigated building roof is completed;(3) refining the building roof by integrating 2D line features observed, automatic image processing or manual measurements, from the images through geometric inference processes. The preliminary experiments show that the proposed CSR algorithm provides a workable platform for building roof reconstruction by fusing 3D line features and 2D image line features. An interactive operating environment is not only advisable when faced with incomplete reconstruction due to the deficiency of automatic systems or data sets but also efficient for improving the quality of building roof model with complete reconstruction, where manual measurements would make up for those insufficiency.

关键词： Roofs

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