Microshift: An Efficient Image Compression Algorithm for Hardware

TL;DR

Microshift is a hardware-efficient image compression algorithm designed for low-power devices, achieving high compression ratios and image quality through innovative micro-shifting and spatial correlation techniques, suitable for wireless sensor networks.

Contribution

The paper introduces Microshift, a novel hardware-friendly image compression algorithm with a co-design approach, outperforming existing methods in power efficiency and compression performance.

Findings

Compresses images to 1.25 bits per pixel with 33.16 dB PSNR.

Demonstrates low hardware complexity and high power efficiency on FPGA and ASIC.

Suitable for low-power wireless vision sensor networks.

Abstract

In this paper, we propose an image compression algorithm called Microshift. We employ an algorithm hardware co-design methodology, yielding a hardware-friendly compression approach with low power consumption. In our method, the image is first micro-shifted, then the sub-quantized values are further compressed. Two methods, the FAST and MRF model, are proposed to recover the bit-depth by exploiting the spatial correlation of natural images. Both methods can decompress images progressively. Our compression algorithm compresses images to 1.25 bits per pixel on average with PSNR of 33.16 dB, outperforming other on-chip compression algorithms. Then, we propose a hardware architecture and implement the algorithm on an FPGA and ASIC. The results on the VLSI design further validate the low hardware complexity and high power efficiency, showing our method is promising, particularly for low-power wireless vision sensor networks.