Robust Coding Over Noisy Overcomplete Channels
| Autor: | Eizaburo Doi, Doru C. Balcan, Michael S. Lewicki |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Speech recognition
Tunstall coding Variable-length code Numerical Analysis Computer-Assisted Signal Processing Computer-Assisted Data Compression Image Enhancement Computer Graphics and Computer-Aided Design Shannon–Fano coding Robustness (computer science) Linear network coding Image Interpretation Computer-Assisted Artifacts Algorithm Algorithms Software Context-adaptive binary arithmetic coding Harmonic Vector Excitation Coding Mathematics Context-adaptive variable-length coding |
| Zdroj: | IEEE Transactions on Image Processing. 16:442-452 |
| ISSN: | 1057-7149 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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