Overview of Research Progress of Digital Image Processing Technology

Abstract

Digital image processing technology has gone through rapid development and is extensively applied in daily life and production, with the rapid development of modern information technology. It plays an inestimable role in remote sensing, medicine, recognition and other fields. This paper briefly introduces the basic concept of digital image processing, summarizes and analyses the commonly used digital image processing technology and the latest scientific research achievements from four aspects, and puts forward the future development direction of digital image processing. In the future, it will pay more attention to artificial intelligence algorithms and achieve better processing results by optimizing the logical structure. By using the simplified image algorithm, the application scope of digital image processing will gradually expand, and will develop in the direction of miniaturization, intelligence, and convenience.

Numerical Simulation of Fatigue Life of Rubber Concrete on the Mesoscale

“…At the stage of concrete modeling, there are two ways of dealing with how to characterize concrete components. One technique is digital image technology recognition [9]. Zheng et al [10] built a 2D concrete mesoscale model based on image recognition and investigated concrete's compressive strength and dimensional effects.…”

Evaluation of quality of computer stored digital images

“…The field of digital image processing has experienced significant advancements and has found widespread applications in various domains such as remote sensing, medicine, and recognition. The forthcoming trajectory of digital image processing will primarily concentrate on artificial intelligence algorithms and enhancing the logical framework, thereby broadening its range of applications and advancing miniaturisation, intelligence, and convenience [10].The primary objectives of the project involve the identification, understanding, and representation of various industry-specific methodologies for quantitatively assessing image quality in different graphic file formats. The evaluation of the quality of digital images stored in computer systems is currently subjective due to the presence of multiple file formats that can be employed for image storage.…”