Frequency-Aware Compressed Video Quality Enhancement via Adaptive Multi-Scale Detail Enhancement

Abstract

Compressed video typically suffers from degraded visual quality due to artifacts such as blurring, blocking effects, and the attenuation of high-frequency details. These distortions make it challenging to accurately restore fine textures using conventional enhancement approaches that rely mainly on spatial domain information, as such methods lack effective modeling of high-frequency components degraded during compression. To address the above limitation, this paper proposes a frequency-aware compressed video quality enhancement framework that improves visual quality by adaptively enhancing high-frequency details and texture structures. The proposed method utilizes multiple consecutive frames and introduces a spatio-temporal feature alignment module to generate aligned features. A multi-scale high-frequency feature extraction strategy is then applied to capture fine details at different scales. Furthermore, an adaptive enhancement mechanism with spatial gating and high-frequency component weighting is proposed to selectively refine high-frequency details and suppress unnecessary enhancement. The frequency-enhanced features are then integrated with aligned features through a gated fusion strategy. Finally, the proposed quality enhancement module predicts a residual map, which is added to the center frame of the input sequence to produce the enhanced output. Experimental results demonstrate that the proposed method effectively reduces compression artifacts and enhances perceptual detail quality compared to existing approaches.