Quantification of smoothing requirement for 3D optic flow calculation of volumetric images

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Quantification of smoothing requirement for 3D optic flow calculation of volumetric images. / Bab-Hadiashar, Alireza; Tennakoon, Ruwan B.; de Bruijne, Marleen.

In: IEEE Transactions on Image Processing, Vol. 22, No. 6, 2013, p. 2128-2137.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Bab-Hadiashar, A, Tennakoon, RB & de Bruijne, M 2013, 'Quantification of smoothing requirement for 3D optic flow calculation of volumetric images', IEEE Transactions on Image Processing, vol. 22, no. 6, pp. 2128-2137. https://doi.org/10.1109/TIP.2013.2246174

APA

Bab-Hadiashar, A., Tennakoon, R. B., & de Bruijne, M. (2013). Quantification of smoothing requirement for 3D optic flow calculation of volumetric images. IEEE Transactions on Image Processing, 22(6), 2128-2137. https://doi.org/10.1109/TIP.2013.2246174

Vancouver

Bab-Hadiashar A, Tennakoon RB, de Bruijne M. Quantification of smoothing requirement for 3D optic flow calculation of volumetric images. IEEE Transactions on Image Processing. 2013;22(6):2128-2137. https://doi.org/10.1109/TIP.2013.2246174

Author

Bab-Hadiashar, Alireza ; Tennakoon, Ruwan B. ; de Bruijne, Marleen. / Quantification of smoothing requirement for 3D optic flow calculation of volumetric images. In: IEEE Transactions on Image Processing. 2013 ; Vol. 22, No. 6. pp. 2128-2137.

Bibtex

@article{c8050d088cfd4e82b56f52da1b783968,
title = "Quantification of smoothing requirement for 3D optic flow calculation of volumetric images",
abstract = "Complexities of dynamic volumetric imaging challenge the available computer vision techniques on a number of different fronts. This paper examines the relationship between the estimation accuracy and required amount of smoothness for a general solution from a robust statistics perspective. We show that a (surprisingly) small amount of local smoothing is required to satisfy both the necessary and sufficient conditions for accurate optic flow estimation. This notion is called 'just enough' smoothing, and its proper implementation has a profound effect on the preservation of local information in processing 3D dynamic scans. To demonstrate the effect of 'just enough' smoothing, a robust 3D optic flow method with quantized local smoothing is presented, and the effect of local smoothing on the accuracy of motion estimation in dynamic lung CT images is examined using both synthetic and real image sequences with ground truth.",
author = "Alireza Bab-Hadiashar and Tennakoon, {Ruwan B.} and {de Bruijne}, Marleen",
year = "2013",
doi = "10.1109/TIP.2013.2246174",
language = "English",
volume = "22",
pages = "2128--2137",
journal = "IEEE Transactions on Image Processing",
issn = "1057-7149",
publisher = "Institute of Electrical and Electronics Engineers",
number = "6",

}

RIS

TY - JOUR

T1 - Quantification of smoothing requirement for 3D optic flow calculation of volumetric images

AU - Bab-Hadiashar, Alireza

AU - Tennakoon, Ruwan B.

AU - de Bruijne, Marleen

PY - 2013

Y1 - 2013

N2 - Complexities of dynamic volumetric imaging challenge the available computer vision techniques on a number of different fronts. This paper examines the relationship between the estimation accuracy and required amount of smoothness for a general solution from a robust statistics perspective. We show that a (surprisingly) small amount of local smoothing is required to satisfy both the necessary and sufficient conditions for accurate optic flow estimation. This notion is called 'just enough' smoothing, and its proper implementation has a profound effect on the preservation of local information in processing 3D dynamic scans. To demonstrate the effect of 'just enough' smoothing, a robust 3D optic flow method with quantized local smoothing is presented, and the effect of local smoothing on the accuracy of motion estimation in dynamic lung CT images is examined using both synthetic and real image sequences with ground truth.

AB - Complexities of dynamic volumetric imaging challenge the available computer vision techniques on a number of different fronts. This paper examines the relationship between the estimation accuracy and required amount of smoothness for a general solution from a robust statistics perspective. We show that a (surprisingly) small amount of local smoothing is required to satisfy both the necessary and sufficient conditions for accurate optic flow estimation. This notion is called 'just enough' smoothing, and its proper implementation has a profound effect on the preservation of local information in processing 3D dynamic scans. To demonstrate the effect of 'just enough' smoothing, a robust 3D optic flow method with quantized local smoothing is presented, and the effect of local smoothing on the accuracy of motion estimation in dynamic lung CT images is examined using both synthetic and real image sequences with ground truth.

UR - http://www.scopus.com/inward/record.url?scp=84875851882&partnerID=8YFLogxK

U2 - 10.1109/TIP.2013.2246174

DO - 10.1109/TIP.2013.2246174

M3 - Journal article

C2 - 23412610

AN - SCOPUS:84875851882

VL - 22

SP - 2128

EP - 2137

JO - IEEE Transactions on Image Processing

JF - IEEE Transactions on Image Processing

SN - 1057-7149

IS - 6

ER -

ID: 51509044