ICHV: A New Compression Approach for Industrial Images

The rapid development of the Industrial Internet of Things and artificial intelligence has brought new pressures to the compression and storage of image information. Thus, efficient image compression approaches are important in the fourth industrial revolution (Industry 4.0), which can save storage resources, accelerate transmission speed, and improve imaging fidelity. In this article, a new approach of image compression based on Haar-V functions (ICHV) is investigated, which has good performance in industrial image compression. The Haar-V functions form a discontinuous orthogonal function system composed of piecewise polynomials. The construction and properties of Haar-V functions are introduced at first. Then, 2-D discrete orthogonal matrices of Haar-V functions and the corresponding image transform method are presented successfully. Finally, a fast computation of ICHV is proposed to enhance the computation speed of image compression. The experimental results indicate that compared with related algorithms, the new approach can effectively improve the quality of compressed images and consume less computational cost.