Video Quality Assessment based on Adaptive Block-size Transform Just-Noticeable Difference model

In this paper, we propose a full reference Video Quality Assessment (VQA) algorithm based on the Adaptive Block-size Transform Just-Noticeable Difference (ABT-JND) model. Firstly, ABT-JND is introduced for its efficiency of modeling the Human Vision System (HVS) characteristics. Based on the ABT-JND model, the full reference VQA is developed, by capturing HVS responses of spatio-temporal distortions over different block-size transforms. Experimental results have demonstrated that the proposed VQA outperforms other VQA methods, while slightly poorer than MOVIE. However, it maintains a very simple formulation. Since the proposed VQA performs on transform domain, it could be easily applied on many related applications, such as video compression, watermarking, and so on.