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Image, Video, and Multidimensional Signal Processing

Tensor Completion via Functional Smooth Component Deflation

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Authors:
Tatsuya Yokota, Andrzej Cichocki
Submitted On:
19 March 2016 - 5:46am
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ICASSP2016_v2.pdf

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[1] Tatsuya Yokota, Andrzej Cichocki, "Tensor Completion via Functional Smooth Component Deflation", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/795. Accessed: Aug. 22, 2017.
@article{795-16,
url = {http://sigport.org/795},
author = {Tatsuya Yokota; Andrzej Cichocki },
publisher = {IEEE SigPort},
title = {Tensor Completion via Functional Smooth Component Deflation},
year = {2016} }
TY - EJOUR
T1 - Tensor Completion via Functional Smooth Component Deflation
AU - Tatsuya Yokota; Andrzej Cichocki
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/795
ER -
Tatsuya Yokota, Andrzej Cichocki. (2016). Tensor Completion via Functional Smooth Component Deflation. IEEE SigPort. http://sigport.org/795
Tatsuya Yokota, Andrzej Cichocki, 2016. Tensor Completion via Functional Smooth Component Deflation. Available at: http://sigport.org/795.
Tatsuya Yokota, Andrzej Cichocki. (2016). "Tensor Completion via Functional Smooth Component Deflation." Web.
1. Tatsuya Yokota, Andrzej Cichocki. Tensor Completion via Functional Smooth Component Deflation [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/795

DICTIONARY LEARNING FOR POISSON COMPRESSED SENSING


Imaging techniques involve counting of photons striking a detector.
Due to fluctuations in the counting process, the measured
photon counts are known to be corrupted by Poisson
noise. In this paper, we propose a blind dictionary learning
framework for the reconstruction of photographic image data
from Poisson corrupted measurements acquired by a compressive
camera. We exploit the inherent non-negativity of the
data by modeling the dictionary as well as the sparse dictionary
coefficients as non-negative entities, and infer these directly

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Authors:
Sukanya Patil, Rajbabu Velmurugan, Ajit Rajwade
Submitted On:
19 March 2016 - 4:43am
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ICASSP_poster.pdf

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[1] Sukanya Patil, Rajbabu Velmurugan, Ajit Rajwade, "DICTIONARY LEARNING FOR POISSON COMPRESSED SENSING", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/791. Accessed: Aug. 22, 2017.
@article{791-16,
url = {http://sigport.org/791},
author = {Sukanya Patil; Rajbabu Velmurugan; Ajit Rajwade },
publisher = {IEEE SigPort},
title = {DICTIONARY LEARNING FOR POISSON COMPRESSED SENSING},
year = {2016} }
TY - EJOUR
T1 - DICTIONARY LEARNING FOR POISSON COMPRESSED SENSING
AU - Sukanya Patil; Rajbabu Velmurugan; Ajit Rajwade
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/791
ER -
Sukanya Patil, Rajbabu Velmurugan, Ajit Rajwade. (2016). DICTIONARY LEARNING FOR POISSON COMPRESSED SENSING. IEEE SigPort. http://sigport.org/791
Sukanya Patil, Rajbabu Velmurugan, Ajit Rajwade, 2016. DICTIONARY LEARNING FOR POISSON COMPRESSED SENSING. Available at: http://sigport.org/791.
Sukanya Patil, Rajbabu Velmurugan, Ajit Rajwade. (2016). "DICTIONARY LEARNING FOR POISSON COMPRESSED SENSING." Web.
1. Sukanya Patil, Rajbabu Velmurugan, Ajit Rajwade. DICTIONARY LEARNING FOR POISSON COMPRESSED SENSING [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/791

CHROMA SCALING FOR HIGH DYNAMIC RANGE VIDEO COMPRESSION


Chroma scaling

Color pixel encoding optimizes the conversion of linear physical values of light into integer values. The efficiency of such encoding methods depends on a trade-off between the bit-depth used and the visible distortion introduced by quantization. This efficiency for different color pixel encoding approaches has been evaluated in literature, without considering the fact that before transmission to the end-user, color encoded content needs to be compressed using a video codec.

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Authors:
Mahsa T. Pourazad, Panos Nasiopoulos
Submitted On:
14 March 2016 - 6:58pm
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Poster_ChrominanceScalingforHDRVideoCompression.pdf

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[1] Mahsa T. Pourazad, Panos Nasiopoulos, "CHROMA SCALING FOR HIGH DYNAMIC RANGE VIDEO COMPRESSION", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/682. Accessed: Aug. 22, 2017.
@article{682-16,
url = {http://sigport.org/682},
author = {Mahsa T. Pourazad; Panos Nasiopoulos },
publisher = {IEEE SigPort},
title = {CHROMA SCALING FOR HIGH DYNAMIC RANGE VIDEO COMPRESSION},
year = {2016} }
TY - EJOUR
T1 - CHROMA SCALING FOR HIGH DYNAMIC RANGE VIDEO COMPRESSION
AU - Mahsa T. Pourazad; Panos Nasiopoulos
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/682
ER -
Mahsa T. Pourazad, Panos Nasiopoulos. (2016). CHROMA SCALING FOR HIGH DYNAMIC RANGE VIDEO COMPRESSION. IEEE SigPort. http://sigport.org/682
Mahsa T. Pourazad, Panos Nasiopoulos, 2016. CHROMA SCALING FOR HIGH DYNAMIC RANGE VIDEO COMPRESSION. Available at: http://sigport.org/682.
Mahsa T. Pourazad, Panos Nasiopoulos. (2016). "CHROMA SCALING FOR HIGH DYNAMIC RANGE VIDEO COMPRESSION." Web.
1. Mahsa T. Pourazad, Panos Nasiopoulos. CHROMA SCALING FOR HIGH DYNAMIC RANGE VIDEO COMPRESSION [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/682

From Pixels to Information Recent Advances in Visual Search

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Authors:
Bernd Girod
Submitted On:
29 February 2016 - 11:22pm
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GlobalSIP_Orlando_Dec2015-small.pdf

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[1] Bernd Girod, "From Pixels to Information Recent Advances in Visual Search", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/606. Accessed: Aug. 22, 2017.
@article{606-16,
url = {http://sigport.org/606},
author = {Bernd Girod },
publisher = {IEEE SigPort},
title = {From Pixels to Information Recent Advances in Visual Search},
year = {2016} }
TY - EJOUR
T1 - From Pixels to Information Recent Advances in Visual Search
AU - Bernd Girod
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/606
ER -
Bernd Girod. (2016). From Pixels to Information Recent Advances in Visual Search. IEEE SigPort. http://sigport.org/606
Bernd Girod, 2016. From Pixels to Information Recent Advances in Visual Search. Available at: http://sigport.org/606.
Bernd Girod. (2016). "From Pixels to Information Recent Advances in Visual Search." Web.
1. Bernd Girod. From Pixels to Information Recent Advances in Visual Search [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/606

Subjective and Objective Quality Assessment of Tone- Mapped Images

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Authors:
Akshai Krishna Manchana, Sai Sheetal Chandra, Sumohana Channappayya, Shanmuganathan Raman
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23 February 2016 - 1:44pm
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1570165825.pdf

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[1] Akshai Krishna Manchana, Sai Sheetal Chandra, Sumohana Channappayya, Shanmuganathan Raman, " Subjective and Objective Quality Assessment of Tone- Mapped Images", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/556. Accessed: Aug. 22, 2017.
@article{556-15,
url = {http://sigport.org/556},
author = {Akshai Krishna Manchana; Sai Sheetal Chandra; Sumohana Channappayya; Shanmuganathan Raman },
publisher = {IEEE SigPort},
title = { Subjective and Objective Quality Assessment of Tone- Mapped Images},
year = {2015} }
TY - EJOUR
T1 - Subjective and Objective Quality Assessment of Tone- Mapped Images
AU - Akshai Krishna Manchana; Sai Sheetal Chandra; Sumohana Channappayya; Shanmuganathan Raman
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/556
ER -
Akshai Krishna Manchana, Sai Sheetal Chandra, Sumohana Channappayya, Shanmuganathan Raman. (2015). Subjective and Objective Quality Assessment of Tone- Mapped Images. IEEE SigPort. http://sigport.org/556
Akshai Krishna Manchana, Sai Sheetal Chandra, Sumohana Channappayya, Shanmuganathan Raman, 2015. Subjective and Objective Quality Assessment of Tone- Mapped Images. Available at: http://sigport.org/556.
Akshai Krishna Manchana, Sai Sheetal Chandra, Sumohana Channappayya, Shanmuganathan Raman. (2015). " Subjective and Objective Quality Assessment of Tone- Mapped Images." Web.
1. Akshai Krishna Manchana, Sai Sheetal Chandra, Sumohana Channappayya, Shanmuganathan Raman. Subjective and Objective Quality Assessment of Tone- Mapped Images [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/556

Face Image Quality Assessment for Face Selection in Surveillance Video using Convolutional Neural Networks

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Authors:
Vignesh Sankar, K. V. S. N. L. Manasa Priya, Sumohana Channappayya
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23 February 2016 - 1:44pm
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1570165667.pdf

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[1] Vignesh Sankar, K. V. S. N. L. Manasa Priya, Sumohana Channappayya, " Face Image Quality Assessment for Face Selection in Surveillance Video using Convolutional Neural Networks", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/555. Accessed: Aug. 22, 2017.
@article{555-15,
url = {http://sigport.org/555},
author = {Vignesh Sankar; K. V. S. N. L. Manasa Priya; Sumohana Channappayya },
publisher = {IEEE SigPort},
title = { Face Image Quality Assessment for Face Selection in Surveillance Video using Convolutional Neural Networks},
year = {2015} }
TY - EJOUR
T1 - Face Image Quality Assessment for Face Selection in Surveillance Video using Convolutional Neural Networks
AU - Vignesh Sankar; K. V. S. N. L. Manasa Priya; Sumohana Channappayya
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/555
ER -
Vignesh Sankar, K. V. S. N. L. Manasa Priya, Sumohana Channappayya. (2015). Face Image Quality Assessment for Face Selection in Surveillance Video using Convolutional Neural Networks. IEEE SigPort. http://sigport.org/555
Vignesh Sankar, K. V. S. N. L. Manasa Priya, Sumohana Channappayya, 2015. Face Image Quality Assessment for Face Selection in Surveillance Video using Convolutional Neural Networks. Available at: http://sigport.org/555.
Vignesh Sankar, K. V. S. N. L. Manasa Priya, Sumohana Channappayya. (2015). " Face Image Quality Assessment for Face Selection in Surveillance Video using Convolutional Neural Networks." Web.
1. Vignesh Sankar, K. V. S. N. L. Manasa Priya, Sumohana Channappayya. Face Image Quality Assessment for Face Selection in Surveillance Video using Convolutional Neural Networks [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/555

Eccentricity Effect of Motion Silencing on Naturalistic Videos

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Authors:
Lawrence K. Cormack, Alan C. Bovik
Submitted On:
23 February 2016 - 1:44pm
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Lark_GlobalSIP_2015.pdf

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[1] Lawrence K. Cormack, Alan C. Bovik, "Eccentricity Effect of Motion Silencing on Naturalistic Videos", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/554. Accessed: Aug. 22, 2017.
@article{554-15,
url = {http://sigport.org/554},
author = {Lawrence K. Cormack; Alan C. Bovik },
publisher = {IEEE SigPort},
title = {Eccentricity Effect of Motion Silencing on Naturalistic Videos},
year = {2015} }
TY - EJOUR
T1 - Eccentricity Effect of Motion Silencing on Naturalistic Videos
AU - Lawrence K. Cormack; Alan C. Bovik
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/554
ER -
Lawrence K. Cormack, Alan C. Bovik. (2015). Eccentricity Effect of Motion Silencing on Naturalistic Videos. IEEE SigPort. http://sigport.org/554
Lawrence K. Cormack, Alan C. Bovik, 2015. Eccentricity Effect of Motion Silencing on Naturalistic Videos. Available at: http://sigport.org/554.
Lawrence K. Cormack, Alan C. Bovik. (2015). "Eccentricity Effect of Motion Silencing on Naturalistic Videos." Web.
1. Lawrence K. Cormack, Alan C. Bovik. Eccentricity Effect of Motion Silencing on Naturalistic Videos [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/554

Locally Linear Low-rank Tensor Approximation

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Authors:
Mark A. Iwen
Submitted On:
23 February 2016 - 1:44pm
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globalsip_snm_alp_v4.pdf

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[1] Mark A. Iwen, "Locally Linear Low-rank Tensor Approximation", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/537. Accessed: Aug. 22, 2017.
@article{537-15,
url = {http://sigport.org/537},
author = {Mark A. Iwen },
publisher = {IEEE SigPort},
title = {Locally Linear Low-rank Tensor Approximation},
year = {2015} }
TY - EJOUR
T1 - Locally Linear Low-rank Tensor Approximation
AU - Mark A. Iwen
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/537
ER -
Mark A. Iwen. (2015). Locally Linear Low-rank Tensor Approximation. IEEE SigPort. http://sigport.org/537
Mark A. Iwen, 2015. Locally Linear Low-rank Tensor Approximation. Available at: http://sigport.org/537.
Mark A. Iwen. (2015). "Locally Linear Low-rank Tensor Approximation." Web.
1. Mark A. Iwen. Locally Linear Low-rank Tensor Approximation [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/537

Edge Preserving Multiscale Image Decomposition with Customized Domain Transform Filters


Edge Preserving Multiscale  Image Decomposition with Customized Domain Transform Filters

In this paper, a multiscale image decomposition method based on domain transform is proposed. The domain transform is a high speed edge preserving smoothing method and can be used to many image processing applications. However, it is highly sensitive to noise. The proposed method is based on filters used in the domain transform but is designed to be robust to noise by employing a multiscale method. An optimization problem is formulated to obtain desired domain- transformed output. As expected, the method can be used to many applications as the domain transform.

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Authors:
Akie Sakiyama, Yuichi Tanaka
Submitted On:
23 February 2016 - 1:44pm
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globalSIP_yagyu.pdf

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[1] Akie Sakiyama, Yuichi Tanaka, "Edge Preserving Multiscale Image Decomposition with Customized Domain Transform Filters", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/487. Accessed: Aug. 22, 2017.
@article{487-15,
url = {http://sigport.org/487},
author = { Akie Sakiyama; Yuichi Tanaka },
publisher = {IEEE SigPort},
title = {Edge Preserving Multiscale Image Decomposition with Customized Domain Transform Filters},
year = {2015} }
TY - EJOUR
T1 - Edge Preserving Multiscale Image Decomposition with Customized Domain Transform Filters
AU - Akie Sakiyama; Yuichi Tanaka
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/487
ER -
Akie Sakiyama, Yuichi Tanaka. (2015). Edge Preserving Multiscale Image Decomposition with Customized Domain Transform Filters. IEEE SigPort. http://sigport.org/487
Akie Sakiyama, Yuichi Tanaka, 2015. Edge Preserving Multiscale Image Decomposition with Customized Domain Transform Filters. Available at: http://sigport.org/487.
Akie Sakiyama, Yuichi Tanaka. (2015). "Edge Preserving Multiscale Image Decomposition with Customized Domain Transform Filters." Web.
1. Akie Sakiyama, Yuichi Tanaka. Edge Preserving Multiscale Image Decomposition with Customized Domain Transform Filters [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/487

Robust Object Tracking via Adaptive Sparse Representation

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23 February 2016 - 1:44pm
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GSIP_tracking_presentation.pdf

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[1] , "Robust Object Tracking via Adaptive Sparse Representation", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/382. Accessed: Aug. 22, 2017.
@article{382-15,
url = {http://sigport.org/382},
author = { },
publisher = {IEEE SigPort},
title = {Robust Object Tracking via Adaptive Sparse Representation},
year = {2015} }
TY - EJOUR
T1 - Robust Object Tracking via Adaptive Sparse Representation
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/382
ER -
. (2015). Robust Object Tracking via Adaptive Sparse Representation. IEEE SigPort. http://sigport.org/382
, 2015. Robust Object Tracking via Adaptive Sparse Representation. Available at: http://sigport.org/382.
. (2015). "Robust Object Tracking via Adaptive Sparse Representation." Web.
1. . Robust Object Tracking via Adaptive Sparse Representation [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/382

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