Adaptive Inter-Mode Decision for HEVC Jointly Utilizing Inter-Level and Spatiotemporal Correlations

Abstract

High Efficiency Video Coding (HEVC) adopts the quadtree structured coding unit (CU), which allows recursive splitting into four equally sized blocks. At each depth level, it enables SKIP mode, merge mode, inter 2N × 2N, inter 2N × N, inter N × 2N, inter 2N × nU, inter 2N × nD, inter nL × 2N, inter nR × 2N, inter N × N (only available for the smallest CU), intra 2N × 2N, and intra N × N (only available for the smallest CU) in inter-frames. Similar to H.264/AVC, the mode decision process in HEVC is performed using all the possible depth levels (or CU sizes) and prediction modes to find the one with the least rate distortion (RD) cost using Lagrange multiplier. This achieves the highest coding efficiency, but leads to a very high computational complexity. Since the optimal prediction mode is highly content dependent, it is not efficient to use all the modes. In this paper, we propose a fast inter-mode decision algorithm for HEVC by jointly using the inter-level correlation of quadtree structure and the spatiotemporal correlation. There exist strong correlations of the prediction mode, the motion vector and RD cost between different depth levels and between spatially temporally adjacent CUs. We statistically analyze the prediction mode distribution at each depth level and the coding information correlation among the adjacent CUs. Based on the analysis results, three adaptive inter-mode decision strategies are proposed including early SKIP mode decision, prediction size correlation-based mode decision and RD cost correlation-based mode decision. Experimental results show that the proposed overall algorithm can save 49%-52% computational complexity on average with negligible loss of coding efficiency, exhibiting applicability to various types of video sequences.

Early CU Depth Decision and Reference Picture Selection for Low Complexity MV-HEVC

“…Therefore, there are some regions normally referred to as boundaries, around which the partition decisions are not the same [13]. Few researchers have used RD cost for the early decision of CUs [22,23]. Lee et al [22] proposed an RD cost-based fast CU decision method, which decides about the skip mode and CU splitting.…”

“…Lee et al [22] proposed an RD cost-based fast CU decision method, which decides about the skip mode and CU splitting. Shen et al [23] proposed three adaptive decision methods, which are early skip mode decision and two decision modes. One is based on prediction size correlation information, while the other is based on RD cost correlation.…”

Fast CU Encoding Schemes Based on Merge Mode and Motion Estimation for HEVC Inter Prediction

“…Shen et al proposed a fast CU size decision method and a fast PU mode decision method for inter prediction in [13] and [14], respectively. In [13], an adaptive CU depth range algorithm was exploited to skip the evaluations of those CU sizes rarely used in the previously coded neighboring CUs.…”

“…In addition, three early termination methods based on motion homogeneity, rate-distortion (RD) cost, and Skip mode, respectively, were proposed to skip the motion estimation on unnecessary CU sizes. These three supplementary information were also utilized to skip the evaluations of unnecessary PU modes for CUs in [14]. However, all these proposed fast algorithms were inefficient for encoding the image regions with inhomogeneous motion activities.…”

Maximum-Entropy-Model-Enabled Complexity Reduction Algorithm in Modern Video Coding Standards

“…In general, the computational complexity of the modern video encoder increases dramatically due to its recursive quad-tree construction. In previous works, the spatial redundancies [2,3], spatio-temporal redundancies [4,5], and visual redundancies [6] were used to reduce the computational complexity of the modern video encoder. However, most of them balance the computational complexity and encoding efficiency unsuccessfully.…”