Search results for " processing"
showing 10 items of 7549 documents
Software for automated application of a reference-based method fora posterioridetermination of the effective radiographic imaging geometry
2005
Objectives: Presentation and validation of software developed for automated and accurate application of a reference-based algorithm (reference sphere method: RSM) inferring the effective imaging geometry from quantitative radiographic image analysis. Methods: The software uses modern pattern recognition and computer vision algorithms adapted for the particular application of automated detection of the reference sphere shadows (ellipses) with subpixel accuracy. It applies the RSM algorithm to the shadows detected, thereby providing threedimensional Cartesian coordinates of the spheres. If the three sphere centres do not lie on one line, they uniquely determine the imaging geometry. Accuracy …
Correction of systematic spatial noise in push-broom hyperspectral sensors: application to CHRIS/PROBA images
2008
Hyperspectral remote sensing images are affected by different types of noise. In addition to typical random noise, nonperiodic partially deterministic disturbance patterns generally appear in the data. These patterns, which are intrinsic to the image formation process, are characterized by a high degree of spatial and spectral coherence. We present a new technique that faces the problem of removing the spatially coherent noise known as vertical striping, usually found in images acquired by push-broom sensors. The developed methodology is tested on data acquired by the Compact High Resolution Imaging Spectrometer (CHRIS) onboard the Project for On-board Autonomy (PROBA) orbital platform, whi…
Introduction to the Issue on Advances in Remote Sensing Image Processing
2011
The papers in this special issue span a wide range of problems arising in modern remote sensing data analysis and provide a snapshot in the state-of-the-art of remote sensing image processing. More advances are expected in the near future, mainly due to the increasing user demands in terms of spatial, spectral, and temporal resolutions of data, and of products generated from these data by automatic processing techniques.
Multimodal biometric recognition systems using deep learning based on the finger vein and finger knuckle print fusion
2020
Recognition systems using multimodal biometrics attracts attention because they improve recognition efficiency and high-security level compared to the unimodal biometrics system. In this study, the authors present a secure multimodal biometrics recognition system based on the deep learning method that uses convolutional neural networks (CNNs). The authors propose two multimodal architectures using the finger knuckle print (FKP) and the finger vein (FV) biometrics with different levels of fusion: the features level fusion and scores level fusion. The features extraction for FKP and FV are performed using transfer learning CNN architectures: AlexNet, VGG16, and ResNet50. The key step aims to …
Recent advances in remote sensing image processing
2009
Remote sensing image processing is nowadays a mature research area. The techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics, and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation…
Atlas selection strategy using least angle regression in multi-atlas segmentation propagation
2011
International audience; In multi-atlas based segmentation propagation, segmentations from multiple atlases are propagated to the target image and combined to produce the segmentation result. Local weighted voting (LWV) method is a classifier fusion method which combines the propagated atlases weighted by local image similarity. We demonstrate that the segmentation accuracy using LWV improves as the number of atlases increases. Under this context, we show that introducing diversity in addition to image similarity by using least-angle regression (LAR) criteria is a more efficient way to rank and select atlases. The accuracy of multi-atlas segmentation converges faster when the atlases are sel…
Ghost Detection and Removal for High Dynamic Range Images: Recent Advances
2012
23 pages; International audience; High dynamic range (HDR) image generation and display technologies are becoming increasingly popular in various applications. A standard and commonly used approach to obtain an HDR image is the multiple exposures fusion technique which consists of combining multiple images of the same scene with varying exposure times. However, if the scene is not static during the sequence acquisition, moving objects manifest themselves as ghosting artefacts in the final HDR image. Detecting and removing ghosting artefacts is an important issue for automatically generating HDR images of dynamic scenes. The aim of this paper is to provide an up-to-date review of the recentl…
Visual Servoing Based on Shifted Moments
2015
Over the past decade, image moments have been exploited in several visual servoing schemes for their ability to represent object regions, objects defined by contours or a set of discrete points. Moments have also been useful to achieve control decoupling properties and to choose a minimal number of features to control the whole degrees of freedom (DOFs) of a camera. However, the choice of moment-based features to control the rotational motions around the $x$ -axis and $y$ -axis simultaneously with the translational motions along the same axis remains a key issue. In this paper, we introduce new visual features computed from low-order “shifted moments invariant.” Importantly, they allow us 1…
The impact of irreversible image data compression on post-processing algorithms in computed tomography
2020
PURPOSE: We aimed to evaluate the influence of irreversible image compression at varying levels on image post-processing algorithms (3D volume rendering of angiographs, computer-assisted detection of lung nodules, segmentation and volumetry of liver lesions, and automated evaluation of functional cardiac imaging) in computed tomography (CT). METHODS: Uncompressed CT image data (30 angiographs of the lower limbs, 38 lung exams, 20 liver exams and 30 cardiac exams) were anonymized and subsequently compressed using the JPEG2000 algorithm with compression ratios of 8:1, 10:1, and 15:1. Volume renderings of CT angiographies obtained from compressed and uncompressed data were compared using objec…
Hardware/Software Implementation of Image Processing Systems Based on ARM Processor
2020
International audience; In this paper we present a hardware/software platform for real-time image processing. We start with the creation of the hardware part based on the ARM processor (PS) with various drivers (PL) for reading, recording and displaying images. Using the SDK tool (Software Development Kit), we add software parts for the realization of some basic image processing algorithms. We use the Xilinx-VIVADO2016 tool for the proposed system design and we use the rapid development board (Xilinx-ZedBoard) for practical implementations. To realize the principle of codesign, we add hardware IPs (RTL level) for the implementation of the same image processing algorithms. To avoid the detai…