Energy Consumption Analysis of Image Encoding and Decoding Algorithms

Context: energy consumption represents an important issue with limited and embedded devices. Such devices, e.g. Smartphones, process many images, both to render the UI and for application specific purposes. Goal: we aim to evaluate the energy consumption of different image encoding/decoding algorithms. Method: we run a series of experiments on a ARM based platform, and we collected the energy consumed in performing typical image encoding and decoding tasks. Result: we found that there is a significant difference among codecs in terms of energy consumption. Most of the energy consumption relates to the computational efficiency of the algorithm (i.e. The time performance) though the type of processing and the algorithm may affect the average power usage up to 37%, thus indirectly affecting the energy consumption. Conclusion: JPEG compression is significantly more energy efficient than PNG both for encoding and decoding. Further studies should focus on the additional features that affect energy consumption beyond computational complexity.