Robust Lightweight Image Compression for MCUs Using Transfer Control via Fuzzy Inference

Abstract

As camera-equipped IoT devices proliferate in bandwidth- and power-constrained environments, the need for ultra-lightweight image compression has become more important than ever before. Recently, MCUCoder achieved efficient adaptive bitrate compression on microcontrollers using an encoder with only 10. 5K parameters. However, that model exhibits limited robustness against dynamic transmission control based on both image content and communication bandwidth. In this paper, we propose Fuzzy-MCUCoder, a model designed to achieve more effective transmission by considering factors such as bandwidth and image complexity. In the proposed model, a fuzzy inference system is incorporated into the encoder that decides the number of channels of the latent representation to be transmitted. As evaluated on the ImageNet dataset, Fuzzy-MCUCoder achieves an improvement in image reconstruction performance under the same transmission time, compared to prior work.