Video file size directly correlates with perceived visual quality
While traditional compression models assume a direct trade-off where higher bitrates or file sizes are needed for better quality, advanced perceptual coding and machine-vision techniques prove that file size and perceived visual quality can be decoupled.
The retrieved literature addresses the relationship between video/image file size (bitrate) and visual quality, primarily through the lens of rate-distortion optimization and perceptual compression. While standard codecs show that reducing file size typically lowers quality, modern perceptual coding algorithms and machine-vision-oriented compression show that file size can be drastically reduced without necessarily degrading perceived or task-relevant visual quality. Therefore, the direct correlation is contested by methods aiming to optimize perceptual quality independently of brute-force file size.
Kau LJ, Tseng CK, Lee MX. Perception-Based H.264/AVC Video Coding for Resource-Constrained and Low-Bit-Rate Applications.. 2025. https://doi.org/10.3390/s25144259
Paper [0] discusses assigning higher bit allocations and dynamic quantization parameters to preserve visual quality, supporting the link between data size/bitrate and fidelity.
Wiseman Y. Achieving Robotic Data Efficiency Through Machine-Centric FDCT Vision Processing.. 2026. https://doi.org/10.3390/s26020518
Paper [1] demonstrates that advanced vision processing and quantization can reduce file size to one-third while preserving highly relevant data for machine vision.
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Qi Liu, Hui Yuan, Raouf Hamzaoui, Honglei Su, Junhui Hou, Huan Yang. Reduced Reference Perceptual Quality Model With Application to Rate Control for Video-Based Point Cloud Compression.. 2021. https://doi.org/10.1109/TIP.2021.3096060
Paper [6] highlights rate-distortion optimization where encoder settings maximize reconstruction quality subject to bitrate constraints.
Yuqi Dai, Changbin Xue, Li Zhou. Visual saliency guided perceptual adaptive quantization based on HEVC intra-coding for planetary images.. 2022. https://doi.org/10.1371/journal.pone.0263729
Paper [7] shows that adaptive quantization techniques can reduce bitrates while maintaining subjective visual quality.
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