For low bit rate video compression, the quality of reconstructed video is usually poor. The high codec priority of region
of interest (ROI) can improve image quality obviously. Nowadays, video segmentation methods are often used for
extracting ROI, but these methods have high computational complexity and are not satisfied to real time communication.
On the other hand, in most existing rate control algorithms, ROI can't select the low and high bit rate R-Q model
adaptively. Aiming at these problems, in this paper, a simple and efficient approach of extracting ROI is proposed which
can decrease the computational complexity of existing ROI extracting algorithms. Bits are distributed to ROI and non-
ROI (NROI) respectively according to the image complexity and motion information. Moreover, the judgment criterion
of distinguishing between low and high bit rate coding category is derived, which makes the algorithm select the R-Q
model adaptively and decrease the rate control errors. In addition, the scheme of modifying the coding order of macro
blocks (MBs) can enhance the objective image quality. Experiment results demonstrate that the proposed algorithm
achieves a bit rate closer to the target, provides fewer skipped frames, and gets better objective and subjective image
quality significantly compared with TMN7 and TMN8 algorithms.