12 papers · ranked by Valyu relevance
Jürgen Seiler, André Kaup
—This paper introduces a framework for distributed parallel image signal extrapolation. Since high-quality image signal processing often comes along with a high computational complexity, a parallel execution is desirable. The proposed framework allows for the application of existing image signal extrapolation…
Xiongtao Ruan, Matthew Mueller, Gaoxiang Liu, Frederik Görlitz + 12 more
Light sheet microscopy is a powerful technique for high-speed 3D imaging of subcellular dynamics and large biological specimens. However, it often generates datasets ranging from hundreds of gigabytes to petabytes in size for a single experiment. Conventional computational tools process such images far slower than the…
Joel Jonsson, Bevan L. Cheeseman, Suryanarayana Maddu, Krzysztof Gonciarz + 1 more
Images Authors: ['Joel Jonsson' 'Bevan L. Cheeseman' 'Suryanarayana Maddu' 'Krzysztof Gonciarz' 'Ivo F. Sbalzarini'] We present data structures and algorithms for native implementations of discrete convolution operators over Adaptive Particle Representations (APR) of images on parallel computer architectures. The APR…
Soundes Oumaima Boufaida, Abdemadjid Benmachiche, Majda Maâtallah
Embedded vision systems need efficient and robust image processing algorithms to perform real-time, with resource-constrained hardware. This research investigates image processing algorithms, specifically edge detection, corner detection, and blob detection, that are implemented on embedded processors, including DSPs…
Maged Abdalla Helmy Abdou, Paulo Ferreira, Eric Jul, Tuyen Trung Truong
'Tuyen Trung Truong'] Abstract—Recent advances in digital imaging, e.g., increased number of pixels captured, have meant that the volume of data to be processed and analyzed from these images has also increased. Deep learning algorithms are state-of-the-art for analyzing such images, given their high accuracy when…
Karl Marrett, Keivan Moradi, Chris Sin Park, Ming Yan + 14 more
Neuronal reconstruction–a process that transforms image volumes into 3D geometries and skeletons of cells– bottlenecks the study of brain function, connectomics and pathology. Domain scientists need exact and complete segmentations to study subtle topological differences. Existing methods are diskbound, dense-access…
Hehai Jiang, Logan A Walker, Ye Li, Bin Duan + 13 more
Recent advances in high throughput optical microscopy have achieved whole-organism scale imaging at diffraction-limited resolutions. Current microscopes, however, require making compromises between achieving the optimal resolution, imaging depth, multispectral capability, and data throughput due to limitations in…
Yichen He, Marco Camaiti, Lucy E. Roberts, James M. Mulqueeney + 2 more
The increased availability of 3D image data requires improving the efficiency of digital segmentation, currently relying on manual labelling, especially when separating structures into multiple components. Automated and semi-automated methods to streamline segmentation have been developed, such as deep learning and…
Jules Scholler, Joel Jonsson, Tomás Jordá-Siquier, Ivana Gantar + 5 more
The large size of imaging datasets generated by next-generation histology methods limits the adoption of those approaches in research and the clinic. We propose pAPRica (pipelines for Adaptive Particle Representation image compositing and analysis), a framework based on the Adaptive Particle Representation (APR) to…
Qiong Chang, Tsutomu Maruyama
—In this paper, we propose a low error rate and realtime stereo vision system on GPU. Many stereo vision systems on GPU have been proposed to date. In those systems, the error rates and the processing speed are in trade-off relationship. We propose a real-time stereo vision system on GPU for the high resolution images.…
Lin Cai, Xuzhong Qu, Hang Zhou, Ning Li + 8 more
High-resolution large-volume biological imaging techniques are now widely used in biological research, but inefficiencies in data processing and visualization persist due to bottlenecks in loading/saving pipelines and limitations of conventional pyramid formats. To address these issues, we have decoupled data loading…
Farahnaz Hosseini, Hossein Ebrahimpour, Samaneh Askari
> Abstract. In this paper, we seek a new method in designing an iris recognition system. In this method, first the Haar wavelet features are extracted from iris images. The advantage of using these features is the high-speed extraction, as well as being unique to each iris. Then the back propagation neural network…