Title :
Maximum entropy image restoration revisited
Author :
Willis, Matthew ; Jeffs, B.D. ; Long, David G.
Author_Institution :
Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA
Abstract :
This paper presents a new non-iterative, closed-form approximation to the maximum entropy (ME) image restoration method. A fast frequency domain implementation of this closed form approach is developed for the case of circular convolutional blur. This result dramatically reduces the computational demands compared to conventional iterative ME algorithms such as MART. Some limitations and advantages of ME restoration are investigated, including its dismal performance for high resolution restoration of decimated or randomly sampled blurred observations
Keywords :
approximation theory; convolution; frequency-domain analysis; image resolution; image restoration; image sampling; iterative methods; maximum entropy methods; MART; circular convolutional blur; computational demands reduction; decimated blurred observations; fast frequency domain implementation; high resolution restoration; maximum entropy image restoration; noniterative closed-form approximation; performance; randomly sampled blurred observations; Constraint optimization; Entropy; Equations; Frequency domain analysis; Image restoration; Iterative algorithms; Least squares approximation; Least squares methods; Null space; Radio astronomy;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.900899
