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Contrast Optimization in a Multi-Windowing Image Processing Architecture

François Berry, Pierre Chalimbaud
2005 IAPR International Workshop on Machine Vision Applications  
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dblp:conf/mva/BerryC05 fatcat:ga5efo4snvd3xm6ep7ms5m2tlu

Multi-GPU Accelerated Parallel Algorithm of Wallis Transformation for Image Enhancement

Han Xiao, Yu-Pu Song, Qing-Lei Zhou
2014 International Journal of Grid and Distributed Computing  
In one word, it has became a high parallelism, multi-threads and multi-core processing unit [11] .  ...  As a result, we propose the parallel algorithm of Wallis transformation based on multiple graphic processing unit (multi-GPU) under Compute Unified Device Architecture (CUDA) in this paper, making use  ...  At present, Related Works The Wallis filter [12] , is a digital processing function that enhances the contrast levels of an image and it can be applied in order to optimize images for subsequent image  ... 
doi:10.14257/ijgdc.2014.7.2.10 fatcat:jtkbru5s4bfj5imjumtys4qrye

A Review: Bilateral Filter for Real Time Image De-noising

Priyanka D. Patil, Dr. Anil D.Kumbhar
2015 International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering  
Bilateral filtering has gained a high awareness level in medical image processing and non-destructive testing.  ...  In this paper a spatially adaptive bilateral filtering image de-noising algorithm with low computational complexity is proposed.  ...  This is in contrast to image enhancement techniques that improve the appearance of an image without reference to a specific model for the degradation process.  ... 
doi:10.15662/ijareeie.2015.0402017 fatcat:wyqf55gnpnhdhpbsh4a4lzcuna

Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters [article]

Axel Barroso-Laguna, Edgar Riba, Daniel Ponsa, Krystian Mikolajczyk
2019 arXiv   pre-print
We introduce a novel approach for keypoint detection task that combines handcrafted and learned CNN filters within a shallow multi-scale architecture.  ...  Results show that our approach outperforms state-of-the-art detectors in terms of repeatability, matching performance and complexity.  ...  across scales, c) a multi-scale feature detection with shallow architecture.  ... 
arXiv:1904.00889v3 fatcat:widyqg6rbrbernaiuvrajrejn4

ReconFormer: Accelerated MRI Reconstruction Using Recurrent Transformer [article]

Pengfei Guo, Yiqun Mei, Jinyuan Zhou, Shanshan Jiang, Vishal M. Patel
2022 arXiv   pre-print
Accelerating magnetic resonance image (MRI) reconstruction process is a challenging ill-posed inverse problem due to the excessive under-sampling operation in k-space.  ...  In particular, the proposed architecture is built upon Recurrent Pyramid Transformer Layers (RPTL), which jointly exploits intrinsic multi-scale information at every architecture unit as well as the dependencies  ...  ReconFormer introduces a powerful locally pyramidal but globally columnar architecture, which can perceive multi-scale representation at any stage while well preserving image details, as shown in Fig.  ... 
arXiv:2201.09376v2 fatcat:x4rwkv5bwvginnnvezyn5atney

Memory Efficient Multi-Scale Line Detector Architecture for Retinal Blood Vessel Segmentation [article]

Hamza Bendaoudi, Farida Cheriet, J. M. Pierre Langlois
2016 arXiv   pre-print
This paper presents a memory efficient architecture that implements the Multi-Scale Line Detector (MSLD) algorithm for real-time retinal blood vessel detection in fundus images on a Zynq FPGA.  ...  The architecture is optimized in terms of resource utilization by reusing the computations and optimizing the bit-width. The throughput is increased by designing fully pipelined functional units.  ...  Section II presents the multi-scale line detector for retinal image blood vessels detection. Section III gives a detailed description of the proposed architecture.  ... 
arXiv:1612.09524v1 fatcat:qyrdlwml55b53eg7rtrgqp75pm

Traffic sign recognition with multi-scale Convolutional Networks

Pierre Sermanet, Yann LeCun
2011 The 2011 International Joint Conference on Neural Networks  
ConvNets are biologically-inspired multi-stage architectures that automatically learn hierarchies of invariant features.  ...  The traditional ConvNet architecture was modified by feeding 1 st stage features in addition to 2 nd stage features to the classifier.  ...  Finding the optimal architecture of a ConvNet for a given task remains mainly empirical. In the next section, we investigate multiple architecture choices. III. EXPERIMENTS A.  ... 
doi:10.1109/ijcnn.2011.6033589 dblp:conf/ijcnn/SermanetL11 fatcat:ee4bzek2qnfdzfnsbggchsvoji

Parallel Harris Corner Detection on Heterogeneous Architecture [chapter]

Yiwei He, Yue Ma, Dalian Liu, Xiaohua Chen
2018 Lecture Notes in Computer Science  
In this paper, we study the parallel method of Harris corner detection and implement it on a heterogeneous architecture using OpenCL.  ...  Corner detection is a fundamental step for many image processing applications including image enhancement, object detection and pattern recognition.  ...  Natural Science Foundation of China (Nos. 61472390, 71731009, 71331005 and 91546201), the Beijing Natural Science Foundation (No.1162005), Premium Funding Project for Academic Human Resources Development in  ... 
doi:10.1007/978-3-319-93701-4_34 fatcat:5yn7b3qthfdedjzag6gsmdvdni

Structural Similarity Loss for Learning to Fuse Multi-Focus Images

Xiang Yan, Syed Zulqarnain Gilani, Hanlin Qin, Ajmal Mian
2020 Sensors  
What is more, we also use the standard deviation of a local window of the image to automatically estimate the importance of the source images in the final fused image when designing the loss function.  ...  In this paper, we present an end-to-end learning approach for directly predicting the fully focused output image from multi-focus input image pairs.  ...  In contrast, a smaller value of Q CV indicates a more improved result. As mentioned earlier, MFNet is an unsupervised multi-focus image fusion technique.  ... 
doi:10.3390/s20226647 pmid:33233568 pmcid:PMC7699701 fatcat:d57k2gutmjeafpfavtfltglglu

Multipatch-GLCM for Texture Feature Extraction on Classification of the Colon Histopathology Images using Deep Neural Network with GPU Acceleration

Toto Haryanto, Adib Pratama, Heru Suhartanto, Aniati Murni, Kusmardi Kusmardi, Jan Pidanic
2020 Journal of Computer Science  
This study proposed advance texture extraction by multi-patch images pixel method with sliding windows that minimize loss of information in each pixel patch.  ...  We use texture feature Gray Level Co-Occurrence Matrix (GLCM) with a meanshift filter as the data pre-processing of the images.  ...  If there is a large amount of variation in an image, the contrast will be high.  ... 
doi:10.3844/jcssp.2020.280.294 fatcat:jxbzrooh4faeldb74vl2vgxazm

Depth and height aware semantic RGB-D perception with convolutional neural networks

Hannes Schulz, Nico Höft, Sven Behnke
2015 The European Symposium on Artificial Neural Networks  
This is especially true when the network is applied in a sliding window. When depth data is available, we can address both problems.  ...  Convolutional neural networks are popular for image labeling tasks, because of built-in translation invariance.  ...  This automatic adjustment is more efficient than sliding windows, because the scale is chosen automatically. In contrast to a multi-scale sliding window, our scale adjustments are continuous. 3.  ... 
dblp:conf/esann/SchulzHB15 fatcat:uv6456wrk5acxm4bblcuf6bxgy

Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation [article]

Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Z. Pan
2021 arXiv   pre-print
Therefore, we propose HRViT, which enhances ViTs to learn semantically-rich and spatially-precise multi-scale representations by integrating high-resolution multi-branch architectures with ViTs.  ...  We balance the model performance and efficiency of HRViT by various branch-block co-optimization techniques.  ...  In contrast, our HRViT adopts a multi-branch topology with enhanced multi-scale representability and improved efficiency.  ... 
arXiv:2111.01236v2 fatcat:pz7p32vrkravlfamypkarp6vl4

A neural network approach using multi-scale textural metrics from very high-resolution panchromatic imagery for urban land-use classification

Fabio Pacifici, Marco Chini, William J. Emery
2009 Remote Sensing of Environment  
This approach also makes it possible to differentiate building architectures, sizes and heights, such as residential houses, apartment blocks and towers with classification accuracies above 0.90 in terms  ...  In this study, very high-resolution panchromatic images from QuickBird and WorldView-1 have been used to accurately classify the land-use of four different urban environments: Las Vegas (U.S.A.), Rome  ...  Acknowledgment The authors would like to thank DigitalGlobe for providing the data used in this paper and also for partially funding Fabio Pacifici. William J.  ... 
doi:10.1016/j.rse.2009.02.014 fatcat:s7haehku7vejnitqnubv7iymyq

Transformer Tracking with Cyclic Shifting Window Attention [article]

Zikai Song and Junqing Yu and Yi-Ping Phoebe Chen and Wei Yang
2022 arXiv   pre-print
In this paper, we propose a new transformer architecture with multi-scale cyclic shifting window attention for visual object tracking, elevating the attention from pixel to window level.  ...  Transformer architecture has been showing its great strength in visual object tracking, for its effective attention mechanism.  ...  In contrast, we use windows with different sizes as heads for multi-scale matching. (3) window shifting is applied differently.  ... 
arXiv:2205.03806v1 fatcat:psfg4bxwmvasllln6jtovq2sfm

Efficient applications in user transparent parallel image processing

F.J. Seinstra, D. Koelma, J.M. Geusebroek, F.C. Verster, A.W.M. Smeulders
2002 Proceedings 16th International Parallel and Distributed Processing Symposium  
Based on experimental results we conclude that our architecture constitutes a powerful and user-friendly tool for obtaining high performance in many important image processing research areas.  ...  Although many image processing applications are ideally suited for parallel implementation, most researchers in imaging do not benefit from high performance computing on a daily basis.  ...  For each orientation step the maximum response is combined in a single contrast image structure.  ... 
doi:10.1109/ipdps.2002.1016511 dblp:conf/ipps/SeinstraKGVS02 fatcat:mnwcfvnvondkjpfuxmb4rwkbwu
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