A background proportion adaptive Lagrange multiplier selection method for surveillance video on HEVC
In the recent video coding standards, the selection of Lagrange multiplier is crucial to achieve trade-off between the choices of low-distortion and low-bitrate prediction modes. For surveillance video coding, the rate-distortion analysis shows that, a larger Lagrange multiplier should be used if the background in a coding unit took a larger proportion. Therefore, a modified Lagrange multiplier might be better for rate-distortion optimization. To address this problem, we perform an in-depth analysis on the relationship between the optimal Lagrange multiplier and the background proportion, and then propose a Lagrange multiplier selection model to obtain the optimal coding performance for surveillance videos. Following this, we further develop a Lagrange multiplier optimized video coding method. Experimental results show that our coding method can averagely achieve 18.07% bitrate saving on CIF sequences and 11.88% on SD sequences against the background-irrelevant Lagrange multiplier selection method.