Optimization of non-uniform grid projection image super-resolution algorithms by reduced granularity and modified addressing

In this work, the factors of reduction of memory requirements and increase in memory traffic associated with the change from reference frame level (baseline algorithm) to macroblock-level for the Super-Resolution (SR) image restoration non-uniform grid projection algorithm are compared over combinations of algorithm parameter values. Then, based on the results of a study on the share of algorithm steps code in the total requirements, the code with larger room for optimization has been identified and optimized. The introduction of a new addressing scheme that takes advantage of the algorithms static characteristics have led to a state in which for 87 out of 96 tested combinations (QCIF frame format) the factor of memory occupancy reduction is greater than the factor of increase in memory traffic. This result opens a way for efficient hardware implementations.