Journal
IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 16, Issue 2, Pages 442-452Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2006.888352
Keywords
channel capacity constraint; channel noise; mean-squared error (MSE) bounds; overcomplete representations; robust coding
Ask authors/readers for more resources
We address the problem of robust coding in which the signal information should be preserved in spite of intrinsic noise in the representation. We present a theoretical analysis for 1- and 2-D cases and characterize the optimal linear encoder and decoder in the mean-squared error sense. Our analysis allows for an arbitrary number of coding units, thus including both under- and over-complete representations, and provides insights into optimal coding strategies. In particular, we show how the form of the code adapts to the number of coding units and to different data and noise conditions in order to achieve robustness. We also present numerical solutions of robust coding for high-dimensional image data, demonstrating that these codes are substantially more robust than other linear image coding methods such as PCA, ICA, and wavelets.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available