Fast Decision of Block size, Prediction Mode and Intra Block for H.264 Intra Prediction Guided by – Dr. K. R. Rao Gaurav Hansda UTA ID – 1000721849 [email protected] OBJECTIVE The objective is to implement a variance-based algorithm for block size decision, an improved filter-based algorithm for prediction mode decision, and a selection algorithm for intra block decision that exploits the relation between the rate-distortion characteristic and the best coding type. All algorithms are to be implemented using JM reference software [17]. This is for the latest video coding standard for H.264 [19]. MOTIVATION The H.264/Advanced video coding (AVC) standard [1] achieves better performance than the previous video coding standards and has become a key technology for multimedia communications and consumer electronics. However, like the other advanced coding techniques adopted earlier, it also brings in significant computational overhead to the encoder. The mode decision of H.264 is more complicated and time-consuming than those of previous coding standards. In fact, it is the most computationally intensive component of an H.264 encoder, more so for the High Profile. Various profiles of H.264 are shown in Fig.1. Therefore, fast algorithms for mode decision are needed. The high performance of this standard is achieved by the adoption of advanced coding tools, such as spatial-domain adaptive intra directional prediction, variable block-size motion estimation (Fig. 2), multiple reference frames, and rate-distortion (R-D) optimization [2], [3]. In particular, the H.264 High Profile is further developed for applications such as professional film production, digital video broadcasting, and high-definition TV and video disc. One notable difference of this new profile is that it adopts the 8×8 intra prediction as a new coding tool to improve the R-D performance. Fig. 3 shows a block diagram of the video coding layer (VCL) for a macroblock [2]. The input video signal is split into macroblocks, the association of macroblocks to slice groups and slices are selected, and then each macroblock of each slice is processed as shown. An efficient parallel processing of macroblocks is possible when there are various slices in the picture.Fig. 1. Profiles in H.264 [17] Fig.2. Segmentations of the macroblock for motion compensation [2]Fig. 3. Basic coding structure for H.264/AVC for a macroblock. [2] As shown in Fig. 4, the mode decision process of an H.264 compliant encoder entails a three-stage hierarchy of operations: inter/intra block decision, block size decision, and prediction mode decision [4]. There are two important implications of this hierarchical structure of mode decision. First, to ensure the correctness of the decision at upper layer and second, to ensure early termination is executed accurately and as early as possible. Most fast mode decision algorithms developed so far, only deal with a single stage of the mode decision hierarchy [5]-[15] and fail to achieve the best possible complexity reduction. In this project more focus is given to left branch of the mode decision hierarchy namely, inter/intra block decision of inter frames, block size decision of intra blocks, and the prediction mode decision of intra blocks. The techniques employed in the proposed algorithms are inspired by several factual observations. For block size decision, it is known that the block size of the best coding mode is highly correlated with texture complexity [16]. In addition, the variance of a macroblock (MB) in the spatial domain, equivalent to the energy of AC components in the discrete cosine transform domain, is a low-cost and effective measurement of texture complexity [16].Fig. 4. Mode decision hierarchy of an H.264 compliant encoder. [4] For prediction mode decision, most filter-based algorithms use edge detectors to determine dominant edges and limit the search of the best prediction mode to those along the detected edges [5]-[12]. However, the information between neighboring blocks is not taken into account. An improved traditional filter-based prediction mode decision algorithm can be obtained by incorporating contextual information [4]. The resulting algorithm works effectively for the High Profile of H.264. When using the Intra4x4 mode, each 4x4 block is predicted from spatially neighboring samples as illustrated in Fig. 4. Eight prediction modes are shown in Fig. 5. Fig. 6 shows a 4x4 luma block that is to be predicted. For the predicted samples [a,b, ... ,p] for the current block, the above and left previously reconstructed samples [A,B, ... ,M] are used according to direction modes. The arrows in Fig. 6 indicate the direction of prediction in each mode. For mode 0 (vertical) and mode 1 (horizontal), the predicted samples are formed by extrapolation from upper samples [A, B, C, D] and from left samples [I, J, K, L], respectively. Fig. 5. Eight “prediction directions” for Intra 4x4 prediction [2].For mode 2 (DC), all of the predicted samples are formed by mean of upper and left samples [A, B, C, D, I, J, K, L]. For mode 3 (diagonal down left), mode 4 (diagonal down right), mode 5 (vertical right), mode 6 (horizontal down), mode 7 (vertical left), and mode 8 (horizontal up), the predicted samples are formed from a weighted average of the prediction samples A–M. For example, samples ‘a’ and ‘d’ are, respectively, predicted by round (I/4 + M/2 + A/4) and round (B/4 + C/2 + D/4) in mode 4, also by round (I/2 + J/2) and round (J/4 + K/2 + L/4) in mode 8. The encoder may select the prediction mode for each block that minimizes the residual between the block to be encoded and its prediction [17]. For prediction of each 8x8 luma block, one mode is selected from the 9 modes, similar to the (4x4) intra-block prediction [17]. For prediction of all 16x16 luma components of a macroblock, four modes are available as shown in Fig. 7. For mode 0 (vertical), mode 1 (horizontal), mode 2 (DC), the predictions are similar with the cases of 4x4 luma block. For mode 4 (plane), a linear ‘plane’ function is fitted to the upper and left-hand samples H and V. This works well in areas of smoothly-varying
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