吉林大学学报(信息科学版) ›› 2025, Vol. 43 ›› Issue (1): 180-186.

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虚拟现实环境下弱小目标图像视觉传达算法研究

张 鹏   

  1. 西安培华学院 建筑与艺术设计学院, 西安 710125
  • 收稿日期:2023-03-08 出版日期:2025-02-24 发布日期:2025-02-24
  • 作者简介:张鹏(1980— ), 男, 西安人, 西安培华学院讲师, 主要从事艺术设计研究, (Tel)86-18966906990(E-mail) sunzhang-2014@ sohu. com。
  • 基金资助:
    陕西省社科界 2022 年度社会科学宣传普及自主基金资助项目(2022KP117)

Research on Visual Communication Algorithm of Weak and Small Target Image in Virtual Reality Environment

ZHANG Peng   

  1. University of Architecture and Art Design, Xi’an Peihua University, Xi’an 710125, China
  • Received:2023-03-08 Online:2025-02-24 Published:2025-02-24

摘要: 为更直观地展现出虚拟图像研究一种虚拟现实环境下弱小目标图像视觉传达算法。 根据目标图像在虚拟环境中成像特点以及影响因素构建图像模型, 依据实际情况和图像模型调整图像目标, 将时域、 空域结合并对空域背景约束, 抑制背景图像, 利用滤波后的图像以及残差背景完成图像去噪。 将上述预处理结果作为基础, 根据目标图像序列运动速度、 特征窗口面积等控制因素, 对图像序列实施采样, 将特征追踪转化为光流计算, 对目标图像实施精确跟踪, 获取光流结果, 实现弱小目标图像视觉传达。 实验结果表明, 该算法视觉传达成功率较高、 用时较短、 完整度较高。

关键词: 虚拟图像, 目标成像, 高斯函数, 时域空域滤波, 特征窗口, 视觉传达

Abstract: In order to show the virtual image more intuitively, a visual communication algorithm for small and weak target images in virtual reality environment is studied. An image model is constructed based on the imaging characteristics and influencing factors of the target image in the virtual environment, the image target is adjusted based on the actual situation and image model, time domain and spatial domain are combined, and the spatial background is constrained to suppress the background image. The filtered image and residual background are used to complete image denoising. Based on the above preprocessing results, and other control factors such as the motion speed of the target image sequence, characteristic window area, and so on, image sequences are sampled, and feature tracking is converted into optical flow calculations, accurately tracking target images, obtaining optical flow results, and achieving visual communication of small and weak target images. Experimental results show that this algorithm has a higher success rate in visual communication, a shorter communication time, and a higher visual communication integrity.

Key words: virtual image, target imaging, gaussian function, time and space domain filtering, feature window, visual communication

中图分类号: 

  • TP391