Study on the Influence of Dynamic Bit Rate Video Compression on the Picture Quality of Film and Television Streaming Media

Streaming media services need to balance video transmission efficiency and picture quality, making variable bitrate (VBR) compression technology a key solution for optimizing resource allocation. This paper systematically analyzes the compression performance of VBR under different resolutions and dynamic scenes based on the H.265/HEVC coding standard, establishing a multi-dimensional image quality evaluation model that integrates PSNR, SSIM, and VMAF metrics to quantify distortion. Experiments configure VBR parameters using the FFmpeg toolchain, analyzing block effects and blurring causes in high-motion scenes, and verifying the adaptive capability of VBR under bandwidth fluctuations. The results show that VBR dynamically adjusts through quantization parameters (QP), improving peak signal-to-noise ratio by 2.3 dB in low-bandwidth scenarios compared to constant bit rate (CBR). However, in high-dynamic scenes, motion estimation strategies need to be optimized to suppress edge distortion. This study provides technical support for streaming platforms to optimize encoding parameters, balance bandwidth costs, and enhance user experience.