Integer Programming Approach to Fixed-rate Entropy-coded Quantization
نویسندگان
چکیده
| This paper describes two new xed-rate entropy-coded quantization methods for stationary memoryless sources where the structure of code-words are derived from a variable-length scalar quantizer. In the rst method, we formulate the quantization as a zero-one integer optimization problem. We show that the resulting integer program can be closely approximated by solving a simple linear program. The result is a Lagrangian formulation which adjoin the constraint (length) to total distortion. Unlike the previous methods with a xed Lagrangian multiplier ( xedslope, and variable rate output), we use an iterative algorithm to optimize Lagrangian function while updating the slope of the function until the cost constraint is satis edwith equality (ensure to be xed-rate). In order to achieve some part of packing gain, we combine the process of trellis encoding with that of quantizer shaping using linear programming. This results in an iterative use of Viterbi algorithm for optimizing the Lagrangian function. For the important class of sources with a monotonically decreasing density, we present another xed-rate method with negligible complexity. Numerical results show an excellent performance with a small complexity for the proposed schemes as compared to previously known methods.
منابع مشابه
A Low Complexity Method for Fixed rate Entropy coded Vector Quantization based on Integer Programming
This paper describes a new approach to Fixed rate Entropy coded Vector Quanti zation FEVQ for stationary memoryless sources where the structure of code words are derived from a variable length scalar quantizer We formulate the quantization search operation as a zero one integer optimization problem and show that the resulting integer program can be closely approximated by solving a simple linea...
متن کاملLattice/Trellis based Fixed-rate Entropy-constrained Quantization
The fixed-rate entropy-constrained vector quantizer draws its motivation from the large gap in the performance of the optimal entropy-constrained scalar quantizer (ESCQ) and the fixed-rate LMQ for most non-uniform sources and tries to bridge this gap while maintaining a fixed-rate output. Having a fixed-rate output avoids all problems associated with a variable rate output such as error propaga...
متن کاملSoft Decision Decoding of a Fixed-rate Entropy-coded Trellis Quantizer over a Noisy Channel
This report presents some new techniques to improve the performance of a Fixedrate Entropy-coded Trellis Quantizer (FE-TCQ) in transmission over a noisy channel. In this respect, we rst present the optimal decoder for a Fixed-rate Entropy-coded Vector Quantizer (FEVQ). A trellis structure is used to model the set of possible codewords in the FEVQ and the Viterbi algorithm is subsequently applie...
متن کاملSoft Decision Decoding of Fixed-rat Entropy-code Trellis Coded Quantization over a Noisy Channel
This paper presents new techniques to improve the performance of a Fixed-rate Entropy-coded Trellis Coded Quantizer (FE-TCQ) in transmission over a noisy channel. In this respect, we first present the optimal decoder for a Fixed-rate Entropy-coded Vector Quantizer (FEVQ). We show that the optimal decoder of the FEVQ can be a maximum likelihood decoder while a trellis structure is used to model ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2001