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Paper Detail

Paper IDS.12.3
Paper Title Registration of Finite Resolution Images: a Second-order Analysis
Authors Ravi Kiran Raman, Analog Devices Inc., United States; Lav Varshney, University of Illinois, Urbana-Champaign, United States
Session S.12: Second-order Analysis
Presentation Lecture
Track Shannon Theory
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Abstract We study the problem of image registration in the finite-resolution regime and characterize the error probability of algorithms as a function of properties of the transformation and the image capture noise. Specifically, we define a channel- aware Feinstein decoder to obtain upper bounds on the minimum achievable error probability under finite resolution. We specifi- cally focus on the higher-order terms and use Berry-Esseen type CLTs to obtain a stronger characterization of the achievability condition for the problem. Then, we derive a strong type-counting result to characterize the performance of the MMI decoder in terms of the maximum likelihood decoder, in a simplified setting of the problem. We then describe how this analysis, when related to the results from the channel-aware context provide stronger characterization of the finite-sample performance of universal image registration.

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2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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