Fast mode decision based on human noticeable luminance difference and rate distortion cost for H.264/AVC

An improved fast and efficient mode decision method for H.264/AVC intracoding is proposed, which is based on the analysis of the gravity center method and more efficient mode selection. In contrast to the fast mode decision method where the intramodes are determined by the gravity center of the block, the mass center vector is computed for the block and the subblocks formed by the proposed subsampling techniques. This method is able to determine all correlation directions of the block that correspond to the intraprediction mode directions of the H.264/AVC. On this basis, only a small number of intraprediction modes are chosen as the best modes for rate-distortion optimization (RDO) calculation. Different video sequences are used to test the performance of the proposed method. Experimental results reveal the significant computational savings achieved with slight peak signal-to-noise ratio (PSNR) degradation and bit-rate increase.

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Fast Mode Decision for HD Scalable Video Coding via Statistical Content Analysis

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s021800141855011x ◽

2018 ◽

Vol 32 (08) ◽

pp. 1855011 ◽

Cited By ~ 1

Author(s):

Yansong Cui ◽

Weizheng Ren ◽

Zhongliang Deng

Keyword(s):

Video Coding ◽

Scalable Video Coding ◽

Rate Distortion ◽

Mode Decision ◽

Scalable Video ◽

Fast Mode ◽

High Definition ◽

Decision Algorithm ◽

Fast Mode Decision ◽

Time Encoding

Scalable video coding (SVC) can provide different bitrate, resolution, or quality formats of the same video through the one-time encoding process. However, SVC also increases encoding complexity significantly, making real-time implementations difficult especially when applied to high definition videos. In this work, we proposed to utilize a fast mode decision algorithm to speed up the SVC encoder. A simple model of the relationship of the video complexity is proposed, the rate-distortion (RD) cost and the statistical mode distribution of the enhancement layer (EL). The proposed mode decision algorithm evaluates the complexity of the video content, then sets the rate distortion RD cost thresholds for inter coding modes. The method also optimizes the process INTRA_BL for I slices. We demonstrate the method using four different resolutions (1080p, 720p, VGA and QVGA), four temporal layers, and two quality layers. We find that the proposed algorithm can reduce the computational complexity significantly while maintaining or even improving encoder efficiency.

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Fast Mode Decision in H.264/AVC

Handheld Computing for Mobile Commerce ◽

10.4018/978-1-61520-761-9.ch021 ◽

2010 ◽

pp. 403-424

Author(s):

Peter Lambert ◽

Stefaan Mys ◽

Jozef Škorupa ◽

Jürgen Slowack ◽

Rik Van de Walle ◽

...

Keyword(s):

Computational Complexity ◽

Video Coding ◽

Optimization Technique ◽

Rate Distortion ◽

Mode Decision ◽

Critical Survey ◽

Fast Mode ◽

Fast Mode Decision ◽

Coding Efficiency ◽

Key Techniques

The latest video coding standard (Wiegand, 2003), H.264/AVC, uses variable block sizes ranging from 16x16 to 4x4 to perform motion estimation in inter-frame coding and a rich set of prediction patterns for intra-frame coding. Then a robust RDO (Rate Distortion Optimization) technique is employed to select the best coding mode and reference frame for each macroblock. As a result, H.264/AVC exhibits high coding efficiency compared to older video coding standards [2, 3] and shows significant future promise in the fields of video broadcasting and communication. However, high coding efficiency also carries high computational complexity. Fast mode decision is one of the key techniques to significantly reducing computational complexity for a similar RD (Rate Distortion) performance. This chapter provides an up-to-date critical survey of fast mode decision techniques for the H.264/AVC standard. The motivation for this chapter is twofold: Firstly to provide an up-to-data review of the existing techniques and secondly to offer some insights into the studies of fast mode decision techniques.

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