TY - JOUR
T1 - An efficient phase and object estimation scheme for phase-diversity time series data
AU - Bardsley, Johnathan M.
PY - 2008
Y1 - 2008
N2 - We present a two-stage method for obtaining both phase and object estimates from phase-diversity time series data. In the first stage, the phases are estimated for each time frame using the limited memory BFGS method. In the second stage, an algorithm that incorporates a nonnegativity constraint as well as prior knowledge of data noise statistics is used to obtain an estimate of the object being observed. The approach is tested on real phase-diversity data with 32 time frames, and a comparison is made between it and a previously developed approach. Also, the image deblurring algorithm in stage two is tested against other standard methods and is shown to be the best for our problem.
AB - We present a two-stage method for obtaining both phase and object estimates from phase-diversity time series data. In the first stage, the phases are estimated for each time frame using the limited memory BFGS method. In the second stage, an algorithm that incorporates a nonnegativity constraint as well as prior knowledge of data noise statistics is used to obtain an estimate of the object being observed. The approach is tested on real phase-diversity data with 32 time frames, and a comparison is made between it and a previously developed approach. Also, the image deblurring algorithm in stage two is tested against other standard methods and is shown to be the best for our problem.
KW - Image deblurring
KW - Nonlinear and nonnegatively constrained optimization
KW - Phase diversity
UR - http://www.scopus.com/inward/record.url?scp=39149119692&partnerID=8YFLogxK
U2 - 10.1109/TIP.2007.912576
DO - 10.1109/TIP.2007.912576
M3 - Article
C2 - 18229800
AN - SCOPUS:39149119692
SN - 1057-7149
VL - 17
SP - 9
EP - 15
JO - IEEE Transactions on Image Processing
JF - IEEE Transactions on Image Processing
IS - 1
ER -