传统感兴趣区域视频编码方法通过整体降低ROI区域的量化参数来实现ROI质量优化，会造成整体率失真性能的下降，尤其在低码率时下降更加严重。针对这一问题，结合人眼掩蔽特性的精细Grid量化方法在文中提出，可有效提高ROI质量并降低整体质量的损失。而且该量化方法能够根据ROI尺寸大小对初始感知权重进行自适应调节，适用于ROI特征不同的视频序列。实验结果表明，对于不同特征的标准测试序列，在中低码率条件下和H.264相比，本文算法能平均提高ROI的PSNR值1.905dB，主观感受有明显提升。和同类ROI算法相比，ROI质量平均提升0.47dB，整体质量提高0.625dB。

Usually， the Region of Interest(ROI) video coding algorithm is implemented by using a smaller quantization parameter(QP) or more bit-plane inside ROI. It caused the degradation of quality by the artifacts of boundary and additional bit-rate burden in ROI. This paper proposes the grid quantization algorithm to avoid these disadvantages. The macroblocks inside of ROI are divided into three kinds: Grid A， Grid B and Gradient. Different partition has different quantization parameter based on visual masking effect. The test results show that the proposed algorithm can promote the ROI objective quality about 1.9dB on average， and the subjective quality is also improved obviously. Compared to other ROI quantization algorithm， the ROI quality is improved by 0.47dB， while the whole picture quality is improved by 0.625dB. The proposed algorithm can reduce the bit-rate burden of ROI and maintain subjective quality.