Flexible Signals and Images Lossless Compression Chip Design for IoT and Industry 4.0

Abstract

This paper presents a lossless compression algorithm and its chip design for signals and images applied to Internet of Things (IoT) and industry 4.0. Since the sensing signals, such as thermal, photo, gas, etc., are important for IoT and industry 4.0, a lossless signal compression technique based on an adaptive prediction and a hybrid entropy coding is proposed in this study. In addition, since applications of images are more and more important for IoT and industry 4.0, a flexible lossless image compression technique based on pixel restoration, median edge detection, and a hybrid entropy coding was developed for the proposed algorithm. The proposed algorithm can provide lossless compression for images in different types which includes grayscale, color (RGB), color filter array (CFA), and infrared images. In order to meet the demands of tiny and low-power-consumption for IoT, the proposed algorithm was realized by VLSI technique. A hardware sharing and pipeline scheduling techniques were used to reduce hardware cost and improve the operating frequency of the proposed design. The proposed design was synthesized by using a TSMC 0.18-$\mu \text{m}$ CMOS process and it contained 5.46 k gate counts. Compared with previous JPEG-LS based designs, this work has benefits of better compression rates, lower cost, lower memory requirement and more lossless compression functions than previous designs. It is suitable for development of IoT and industry 4.0.