Leida xuebao (Apr 2024)

Preliminary Research on the Effectiveness of Gestalt Perceptual Principles in SAR Images

  • Ruixi YOU,
  • Yutong QIAN,
  • Feng XU

DOI
https://doi.org/10.12000/JR23187
Journal volume & issue
Vol. 13, no. 2
pp. 345 – 358

Abstract

Read online

Synthetic Aperture Radar (SAR) images are an important data source in microwave vision research; however, computer vision cannot interpret these images effectively based on optical perceptual principles. Therefore, microwave vision, which draws inspiration from human visual perception principles and combines computer vision techniques with electromagnetic physical principles, has become an important research direction in microwave remote sensing. Exploring the cognitive basis for microwave vision is crucial for improving the theoretical system of microwave vision. Therefore, as a preliminary attempt to enhance the theoretical understanding of microwave vision, this paper examines the effectiveness of optical perceptual principles for microwave vision. As a classical visual theory, Gestalt perceptual principles are commonly used for describing the perceptual principles of the human visual system for the external optical world and are a cognitive theoretical foundation of computer vision. In this context, this paper uses SAR images as the research object, focuses on the design process of cognitive psychology experiments, and preliminarily studies the effectiveness of Gestalt perceptual principles for SAR images, including the principles of perceptual grouping and perceptual invariance, exploring the cognitive basis of microwave vision. The experimental results indicate that the Gestalt perceptual principles cannot be directly applied to the algorithm design for SAR images, and the knowledge concepts and visual principles derived from the optical world using the human visual system do not perform well in SAR images. In the future, it will be necessary to summarize the corresponding visual cognitive principles based on the characteristics of microwave images, such as SAR images.

Keywords