关键词: 闪烁干扰, 质量评价, 无参考, 拉普拉斯分布, 最小可见差异值

Abstract:

Temporal flickering in the video is a key factor of affecting the quality of video. Accurate identification of temporal flickering is required for the automatic analysis and diagnosis of video quality. Moreover, it can be integrated with artifact removal and quality enhancement algorithms to promote the adaptivity of the proposed algorithm. A study of temporal flickering in video surveillance was given to demonstrate that the differential signal of temporal flickering in time domain follows the Laplacian distribution. Motivated by this statistical observation and the idea of small probability events, the proposed method iteratively segmented differential signal of motion in foreground, which affected the identification of temporal flickering. Furthermore, the proposed approach exploited the Just-Noticeable Difference (JND) mechanism of the human visual system to identify the temporal flickering using the flickering frequency and amplitude. The proposed method yielded superior performance to that of the conventional Gaussian Mixture model to achieve more accurate classification of the normal video and temporal flickering video, as verified in the ROC (Receiver Operating Characteristic) curve presented in experimental results. The proposed no-reference algorithm is able to achieve fairly good performance in temporal flickering identification.

Key words: temporal flickering, quality assessment, no-reference, Laplacian distribution, Just-Noticeable Difference (JND)