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Efficient deinterlacing method using simple edge slope tracing

Sajid Khan, Dongho Lee
2015 Optical Engineering: The Journal of SPIE  
Applying averaging, or any linear algorithm, achieves time-efficient deinterlacing but produces artifacts.  ...  Deinterlacing, which converts an interlaced video into a progressive video, is a problem in image interpolation that doubles the number of vertical lines.  ...  Binary patterns, 9 gradient-guided deinterlacing (GGD), 12 deinterlacing with closeness and similarity 14 and the moving least-squares method (MLSM) 15 have also been suggested as methods to accurately  ... 
doi:10.1117/1.oe.54.10.103108 fatcat:xdoe6dpg7fc5pdxwxpi7y5h4eq

An HVS-inspired video deinterlacer based on visual saliency

Umang Aggarwal, Maria Trocan, Francois-Xavier Coudoux
2016 Vietnam Journal of Computer Science  
In this paper, a spatial saliency-guided motion-compensated deinterlacing method is proposed which accounts for the properties of the Human Visual System (HVS): our algorithm classifies the field according  ...  Video deinterlacing is a technique wherein the interlaced video format is converted into progressive scan format for nowadays display devices.  ...  Conclusion In this paper, a spatial saliency-guided motion-compensated method for video deinterlacing is proposed.  ... 
doi:10.1007/s40595-016-0081-1 fatcat:xwqxl55qazcthj5gu25vaerm44

Speeding up motion estimation in modern video encoders using approximate metrics and SIMD processors

Steven Pigeon, Stephane Coulombe
2009 2009 IEEE Symposium on Industrial Electronics & Applications  
In the past, efforts have been devoted to the amelioration of motion estimation algorithms to speed up motion compensated video coding.  ...  The resilience of motion estimation algorithms to various error metrics allows us to propose new high performance approximate metrics based on the sum of absolute differences (SAD).  ...  through a gradient descent type search guided by a predictive algorithm that estimates the general vicinity of the optimal solution-the effects of the metrics used for error estimation have received less  ... 
doi:10.1109/isiea.2009.5356471 fatcat:3ppejusigvh2hgqgen3dwp7yue

Image interpolation with hidden Markov model

Amin Behnad, Xiaolin Wu
2010 2010 IEEE International Conference on Acoustics, Speech and Signal Processing  
A new image interpolation algorithm is developed that combines optimal data fusion and context modeling of images.  ...  The main part of this thesis is devoted to a more sophisticated image interpolation algorithm based on hidden Markov modeling (HMM).  ...  Fusion Based Deinterlacing Algorithm As argued so far, the accuracy of edge-guided deinterlacing algorithms mainly depends on the discriminant applied to find the best interpolation direction.  ... 
doi:10.1109/icassp.2010.5495234 dblp:conf/icassp/BehnadW10 fatcat:ydnttcegujfpboqrs3usy7rmwy

Improving image-guided radiation therapy of lung cancer by reconstructing 4D-CT from a single free-breathing 3D-CT on the treatment day

Guorong Wu, Jun Lian, Dinggang Shen
2012 Medical Physics (Lancaster)  
The reconstructed 4D-CT using our algorithm shows clinically acceptable accuracy and could be used to guide a more accurate patient setup than the conventional method.  ...  Promising reconstruction results imply the possible application of this new algorithm in the image guided radiation therapy of lung cancer.  ...  On the treatment day, a free-breathing 3D-CT image will be acquired for image-guided patient setup.  ... 
doi:10.1118/1.4768226 pmid:23231317 pmcid:PMC3528792 fatcat:qtl274o5zjat5daptnixhgrewm

Near-lossless image compression: minimum-entropy, constrained-error DPCM

Ligang Ke, M.W. Marcellin
1998 IEEE Transactions on Image Processing  
A set of "contexts" is defined for the conditioning prediction error model and an algorithm that produces minimum entropy conditioned on the contexts is presented.  ...  With a "near-lossless" criterion of no more than a d gray-level error for each pixel, where d is a small nonnegative integer, trellises describing all allowable quantized prediction error sequences are  ...  It has been analyzed what would become the quantization noise applied to the interlaced image after a deinterlacing operation.  ... 
doi:10.1109/83.660999 pmid:18267396 fatcat:ylysz3gnyjefdbwrvssspbqqri

A Variational Method for Dejittering Large Fluorescence Line Scanner Images

Hoai-Nam Nguyen, Vincent Paveau, Cyril Cauchois, Charles Kervrann
2018 IEEE Transactions on Computational Imaging  
a proximal algorithm for the convex part and the other using an exhaustive search for the non-convex part.  ...  An energy functional composed of a re-alignment criterion and a differential-based regularizer is especially designed.  ...  We note that the projected gradient descent algorithm is a particular case of the forwardbackward algorithm [32, 24] . This algorithm also belongs to the family of proximal algorithms [26] .  ... 
doi:10.1109/tci.2018.2818017 fatcat:qg66q4rwqre4xa5jtfh5o2li3i

Human Body Reconstruction from Image Sequences [chapter]

Fabio Remondino
2002 Lecture Notes in Computer Science  
In this paper a method for the 3-D reconstruction of static human body shapes from images acquired with a video-camera is presented.  ...  In particular, a topic of great interest is the modeling of real humans.  ...  Then the median of this sum of disparity gradients is found, and those matches that have a disparity gradient sum greater than this median sum are removed.  ... 
doi:10.1007/3-540-45783-6_7 fatcat:y76nwgmt5vbonp6mdxd53wovi4

Urban road user detection and classification using 3D wire frame models

N. Buch, J. Orwell, S.A. Velastin
2010 IET Computer Vision  
This aims to guide surveillance operators and reduce human resources for observing hundreds of cameras in urban traffic surveillance.  ...  The full system including detection and classification achieves a recall of 87% at a precision of 85.5% outperforming similar systems in the literature.  ...  filter algorithms: shadow removal (Sr), shadow removal with de-interlacing (Sr+Di), deinterlacing (Di) and no filter (-).  ... 
doi:10.1049/iet-cvi.2008.0089 fatcat:3nckx3eqt5hiditz67rx4qslby

Color interpolation algorithm for an RWB color filter array including double-exposed white channel

Ki Sun Song, Chul Hee Park, Jonghyun Kim, Moon Gi Kang
2016 EURASIP Journal on Advances in Signal Processing  
The red and blue channels are interpolated by applying a guided filter that uses the interpolated white channel as a guided value.  ...  In this paper, we propose a color interpolation algorithm for a red-white-blue (RWB) color filter array (CFA) that uses a double exposed white channel instead of a single exposed green (G) channel.  ...  deinterlacing algorithm (CM3) [24] , which uses the characteristic of this CFA pattern with sampled W only in the even row; and a method (CM4) that modifies the algorithm for the existing Bayer CFA such  ... 
doi:10.1186/s13634-016-0359-6 fatcat:vdjl3qjtr5gcnfokhn7q5zlc2u

Automated working distance adjustment enables optical coherence tomography of the human larynx in awake patients

Sabine Donner, Sebastian Bleeker, Tammo Ripken, Martin Ptok, Michael Jungheim, Alexander Krueger
2015 Journal of Medical Imaging  
Therefore, an automatic compensation of movements was implemented into a swept source OCT-laryngoscope. Video and OCT beam path were combined in one tube of 10-mm diameter.  ...  Segmented OCT images served as distance sensor and a feedback control adjusted the working distance between 33 and 70 mm by synchronously translating the reference mirror and focusing lens.  ...  Acknowledgments Part of this work was supported by the Federal Ministry of Economics and Technology on the basis of a decision by the German Bundestag (AiF Grant No. 17132N).  ... 
doi:10.1117/1.jmi.2.2.026003 pmid:26158116 pmcid:PMC4481024 fatcat:4dngsbrwvjgm5hfyfqh2erxlyi

Local object-based super-resolution mosaicing from low-resolution video

Petra Krämer, Jenny Benois-Pineau, Jean-Philippe Domenger
2011 Signal Processing  
artifacts [16], and deinterlacing [37].  ...  A gradient-based shift estimator is used in [48] 23 for object motion. Moreover, in [48, 31] the problem of super-resolving very 24 small objects is addressed.  ...  A.4.jugated gradient method is much slower than the steepest descent method, but the accelerate gradient descent was shown to be two times faster than the steepest descent method.  ... 
doi:10.1016/j.sigpro.2011.02.001 fatcat:ttdioeowujewfa6hasensutvam

Automatically detecting the small group structure of a crowd

Weina Ge, Robert T. Collins, Barry Ruback
2009 2009 Workshop on Applications of Computer Vision (WACV)  
These groups are discovered using a bottom-up hierarchical clustering approach that compares sets of individuals based on a generalized, symmetric Hausdorff distance defined with respect to pairwise proximity  ...  Building upon state-of-the-art algorithms for pedestrian detection and multi-object tracking, and inspired by social science models of human collective behavior, we automatically detect small groups of  ...  There is recent evidence that more efficient recognition of group activities is possible by using a model of the group activity process to guide interpretation of the actions of individual members [30  ... 
doi:10.1109/wacv.2009.5403123 dblp:conf/wacv/GeCR09 fatcat:pne4earbwbayxj6ywxlomfrrni

Infrared Imagery of Crown-Fire Dynamics during FROSTFIRE

Janice Coen, Shankar Mahalingam, John Daily
2004 Journal of applied meteorology (1988)  
A thorough understanding of crown-fire dynamics requires a clear picture of the three-dimensional winds in and near the fire, including the flaming combustion zone and the convective updrafts produced  ...  These observations and analyses present a unique high-spatial-resolution and high-temporal-resolution perspective of the motions within crown fires propagating up a forested 20Њ slope under light winds  ...  To extract more information beyond the evolution of tem- VOLUME 43 J O U R N A L O F A P P L I E D M E T E O R O L O G Y perature, one must make further assumptions and apply analysis algorithms, described  ... 
doi:10.1175/1520-0450(2004)043<1241:iiocdd>;2 fatcat:lrww5jvy5jay7o3lic6fpexsbq

Deep Learning for HDR Imaging: State-of-the-Art and Future Trends [article]

Lin Wang, Kuk-Jin Yoon
2021 arXiv   pre-print
In recent years, there has been a significant advancement in HDR imaging using deep learning (DL).  ...  Importantly, we provide a constructive discussion on each category regarding its potential and challenges.  ...  Therefore, a joint deinterlacing and denoising framework is designed to reconstruct a noise-free HDR image.  ... 
arXiv:2110.10394v3 fatcat:pvsktnd5wrgo5lstughzlhon7i
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