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Lower bound on average mean-square error for image restoration

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1 Author(s)
Hsien-Sen Hung ; Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA

An average mean-square error bound that is applicable to general image observation models involving degradations of blur, signal-dependent and signal-independent noise, and sensor nonlinearity is derived. A Cramer-Rao lower bound on average mean-square errors for any unbiased image restoration scheme is derived. This bound is analytically expressed as a function of degradation parameters of imaging systems. Potential performance improvements by incorporating signal-dependent noise or sensor nonlinearity into algorithmic design are discussed

Published in:

Signal Processing, IEEE Transactions on  (Volume:39 ,  Issue: 2 )