TY - GEN A1 - Herglotz, Christian A1 - Kränzler, Matthias A1 - Xu, Bide A1 - Kaup, André T1 - Decoding Energy Optimization for Video Coding Using Model-Driven Gradient Descent T2 - IEEE 26th International Workshop on Multimedia Signal Processing (MMSP) N2 - Nowadays, a large part of the global energy consumption caused by video communications can be attributed to end-user devices such as smartphones, tablet PCs, and TV sets. In this paper, we present a method to increase the performance of an existing algorithm dedicated to reduce the end-user side energy consumption during video streaming. The algorithm, which is called decoding-energy-rate-distortion optimization (DERDO), exploits a decoding energy model during encoding and chooses coding modes in such a way that the software decoding energy is minimized. In this paper, we develop a dedicated gradient descent approach for DERDO that refines specific energy coefficients used for decoding energy modeling. We find that this approach boosts the performance of DERDO by increasing the energy savings by at least 5% with respect to standard DERDO. As a consequence, we observe decoding energy savings of more than 40% and more than 7% for practical encoder and decoder implementations of HEVC and H.264/AVC, respectively, when compared to standard encoding using classic rate-distortion optimization. KW - Energy consumption KW - Energy conservation KW - Software algorithms KW - Signal processing algorithms KW - Streaming media KW - Encoding KW - Software KW - Decoding KW - Optimization Y1 - 2024 SN - 979-8-3503-8725-4 SN - 979-8-3503-8726-1 U6 - https://doi.org/10.1109/MMSP61759.2024.10743503 SN - 2473-3628 SN - 2163-3517 ER -