Decoder energy-aware intra-coded HEVC bit stream generation

Abstract

The rising demand for media consumption via mobile devices and the emergence of complex video coding algorithms present an additional challenge for the energy management algorithms in resourceconstrained consumer electronic devices. Thus, generating energyoptimized video bit streams will positively contribute towards overcoming this challenge. This paper introduces a novel energy model for intra-frame decoding of HEVC encoded video that predicts the decoding energy of a coding unit. Thereafter, a novel energy-ratedistortion optimized coding mode selection algorithm is proposed to generate energy-efficient bit streams using the proposed energy model within the encoder. The proposed energy model is shown to predict the decoding energy of a coding unit with an average error less than 2%. Moreover, the proposed coding mode selection algorithm achieves an average 10.8% reduction in the energy consumed at the decoder with a-0.25 dB impact to the Bjøntegaard Delta-Peak Signal-to-Noise Ratio.

A feature based complexity model for decoder complexity optimized HEVC video encoding

“…Furthermore, the complexity associated with the transform coefficient decoding, e coef f , can be modeled as a linear function of the number of non-zero transform coefficients [10]. In addition, the decoder complexity model and the profiling details for intra-predicted CUs are derived based on the information presented in [15].…”

Decoding-Complexity-Aware HEVC Encoding Using a Complexity–Rate–Distortion Model

“…To this end, a decoding complexity profiling for individual decoding operations relating to the HEVC coding modes and features has been carried out in our previous works [27][28] using open source instruction level profiling tools [34]. In this context, the computational complexities in terms of CPU cycles identified in [27] [28] are embedded within HM16.0 implementation to make the encoder aware of the relative complexities of the decoding operations (The CU level decoding complexity estimation models in [27] and [28] for intra-and inter-prediction, respectively, have been verified to predict the decoding complexity within the encoder with only < 5% prediction error). The encoder now possesses the resulting bit rate, distortion and decoding complexity for a particular coding mode and QP of a given content which can then be used to form the decoding complexity, rate and distortion analysis, as described next.…”

“…The energy consumption during the whole decoding and playback process is measured in terms of the reduction in battery capacity via Linux's power measurement tools. The energy consumed for each QP (22,27,32,37) is recorded and together with decoded stream's PSNR is used to calculate BD-E which represents the energy consumed to achieve the same video quality as the reference HM 16.0 generated bit streams. The energy reduction under these conditions with different 17.54 * BD-C (%) achieved when using HM 16.0 reference decoder.…”

“…This is aided by the use of more detailed and accurate HEVC decoding complexity estimation models [27][28] which yield more accurate decoding complexity estimations for the decoding complexity rate distortion optimization in (2).…”

“…The proposed algorithm is implemented in the HM 16.0 reference software [31], where the complexity models presented in [27][28] perform the decoding complexity estimations and the proposed Lagrangian cost function in (2) determines the coding modes for both inter-and intraprediction (Fig. 4).…”