Content-Split Block Search Algorithm Based High Efficiency Video Coding

690-693In this paper, the video streaming generation in H.265 using novel technique based on content split block (CSB) search algorithm is presented. The proposed algorithm exploits the Inter and Intra prediction through motion estimation and compensation (IPME) encoded to use four different QPs: 22, 27, 32, and 37, during the redundancy analysis in order to improve the quality of video frame encoded. The proposed algorithm exhibits the useful property of block structure based on content-tree representation for each and every frame to IPME coded without affecting either the bit rate of video stream and perceptual quality of the video frame. The proposed Search algorithm improves the visual quality of coded video frame and reduces the blocking artefacts of video frame passed through multi-stages of H.265

Rate control for HEVC intra-coding based on piecewise linear approximations

This paper proposes a rate control (RC) algorithm for intra-coded sequences (I-frames) within the context of block-based predictive transform coding (PTC) that employs piecewise linear approximations of the rate-distortion (RD) curve of each frame. Specifically, it employs information about the rate (R) and distortion (D) of already compressed blocks within the current frame to linearly approximate the slope of the corresponding RD curve. The proposed algorithm is implemented in the High-Efficiency Video Coding (HEVC) standard and compared with the current HEVC RC algorithm, which is based on a trained rate lambda (R-λ) model. Evaluations on a variety of intra-coded sequences show that the proposed RC algorithm not only attains the overall target bit rate more accurately than the current RC algorithm but is also capable of encoding each I-frame at a more constant bit rate according to the overall bit budget, thus avoiding high bit rate fluctuations across the sequence

QVRF: A Quantization-error-aware Variable Rate Framework for Learned Image Compression

Learned image compression has exhibited promising compression performance, but variable bitrates over a wide range remain a challenge. State-of-the-art variable rate methods compromise the loss of model performance and require numerous additional parameters. In this paper, we present a Quantization-error-aware Variable Rate Framework (QVRF) that utilizes a univariate quantization regulator a to achieve wide-range variable rates within a single model. Specifically, QVRF defines a quantization regulator vector coupled with predefined Lagrange multipliers to control quantization error of all latent representation for discrete variable rates. Additionally, the reparameterization method makes QVRF compatible with a round quantizer. Exhaustive experiments demonstrate that existing fixed-rate VAE-based methods equipped with QVRF can achieve wide-range continuous variable rates within a single model without significant performance degradation. Furthermore, QVRF outperforms contemporary variable-rate methods in rate-distortion performance with minimal additional parameters.Comment: 7 pages, 6 figure

Decoding-complexity-aware HEVC encoding using a complexity–rate–distortion model

The energy consumption of Consumer Electronic (CE) devices during media playback is inexorably linked to the computational complexity of decoding compressed video. Reducing a CE device's the energy consumption is therefore becoming ever more challenging with the increasing video resolutions and the complexity of the video coding algorithms. To this end, this paper proposes a framework that alters the video bit stream to reduce the decoding complexity and simultaneously limits the impact on the coding efficiency. In this context, this paper (i) first performs an analysis to determine the trade-off between the decoding complexity, video quality and bit rate with respect to a reference decoder implementation on a General Purpose Processor (GPP) architecture. Thereafter, (ii) a novel generic decoding complexity-aware video coding algorithm is proposed to generate decoding complexity-rate-distortion optimized High Efficiency Video Coding (HEVC) bit streams. The experimental results reveal that the bit streams generated by the proposed algorithm achieve 29.43% and 13.22% decoding complexity reductions for a similar video quality with minimal coding efficiency impact compared to the state-of-the-art approaches when applied to the HM16.0 and openHEVC decoder implementations, respectively. In addition, analysis of the energy consumption behavior for the same scenarios reveal up to 20% energy consumption reductions while achieving a similar video quality to that of HM 16.0 encoded HEVC bit streams