|Edge is an important feature in video classification which finds applications in video representation and coding. In H.264/AVC, intra prediction mode decision (a computationally intensive process) is based on the orientation of the edges in the macroblock. In this paper, we first investigate the difference properties derived from three coefficients in the non-normalized Haar transform (NHT) domain and present a fast and efficient method to classify block edge using these properties. The proposed method significantly reduces the number of computational operations in the edge models determination with no multiplications and less addition operations. The use of edge classification for fast intra prediction mode decision in H.264/AVC video coding is then presented. The experimental results show the effectiveness of the proposed method.|
Hongliang Li, King N. Ngan, and Zhenyu Wei, “Fast and efficient method for block edge classification and its application in H.264/AVC video coding”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 18, no.6, pp. 756-768, 2008.
|As shown in Fig. 1, let θ denote the edge orientation in the given block. Based on the above difference information in the coefficients, we can derive the some rules for its estimation.|
Fig. 1. Possible edge orientation in the given block.
|Finally, based on the above analysis, we summarize the proposed edge classification algorithm, as depicted in Fig. 2, in which there are a total of 42 edge models that can be determined from three NHT coefficients. Each step in the classification process, such as EM!EMA, EMA!EMA-I, corresponds to a certain criterion defined in this paper. The detailed representation range of each model is described in Table I.|
Fig. 2 The framework of the proposed edge classification method.
Fig. 3 Experimental results for Lena (a) and Peppers (d) images. (a) and (d): The original image. (b) and (e): Edge classification for 8 x 8 image block. (c) and (f): Edge classification for 4 x 4 image block.
|We develop a fast mode decision algorithm in H.264/AVC intra prediction based on our proposed edge classification method. The results are shown in Table VI.|
|1. Source Code (MATLAB)|
|Source code can be downloaded from|
|This work was partially supported by research grants from the Shun Hing Institute of Advanced Engineering, and the Chinese University of Hong Kong Focused Investment Scheme (Project 1903003).|