Title :
Optimal bit allocation under multiple rate constraints
Author_Institution :
Signal & Image Process. Inst., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
We present a new Lagrangian-based iterative technique for rate-distortion optimization under multiple rate constraints. We show how for sets of “linear” constraints this technique can be proven to be optimal up to a convex hull approximation. As an application we consider the problem of optimal buffer-constrained bit allocation. Our technique can be used to find an excellent approximation to the solutions achieved using dynamic programming. In cases where the buffer size is relatively large our approach shows a significant reduction in complexity as compared to dynamic programming
Keywords :
computational complexity; data compression; encoding; iterative methods; optimisation; rate distortion theory; Lagrangian-based iterative technique; convex hull approximation; dynamic programming; encoding; linear constraints; multiple rate constraints; optimal bit allocation; optimal buffer-constrained bit allocation; rate-distortion optimization; Bit rate; Constraint optimization; Delay systems; Dynamic programming; Image coding; Image processing; Lagrangian functions; Limiting; Rate-distortion; Signal processing;
Conference_Titel :
Data Compression Conference, 1996. DCC '96. Proceedings
Conference_Location :
Snowbird, UT
Print_ISBN :
0-8186-7358-3
DOI :
10.1109/DCC.1996.488340