A Non-Iterative R-D Optimization Algorithm for Rate-Constraint Problems

R-D optimization algorithm is frequently used where subband coding or vector quantization is required. All existing R-D optimization algorithms have an iterative process which results in more computational complexity and execution time. In this paper we propose a novel R-D optimization algorithm that has a non-iterative process with lower computational complexity. This algorithm is based on exponential modeling of R-D curves and can be used in rate-constraint problems. The proposed algorithm presents a good performance with non-convex curves as well as convex ones. While the execution time of the existing algorithms is O(N_crv×N_pt), the execution time of the proposed algorithm is O(N_crv), where N_crv is the number of curves and N_pt is the average number of points in each curve. The quality degradation is 0.32 dB, in average, when it is tested in the rate control component of a JPEG2000 encoder.