Open Access

ARTICLE

Enhancing Military Visual Communication in Harsh Environments Using Computer Vision Techniques

Shitharth Selvarajan^1,2,3,*, Hariprasath Manoharan⁴, Taher Al-Shehari⁵, Nasser A Alsadhan⁶, Subhav Singh^7,8

1 School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds, LS6 3HF, UK
2 Department of Computer Science and Engineering, Chennai Institute of Technology, Chennai, 600069, India
3 Centre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, India
4 Department of Electronics and Communication Engineering, Panimalar Engineering College, Poonamallee, Chennai, 600123, India
5 Computer Skills, Department of Self-Development Skill, Common First Year Deanship, King Saud University, Riyadh, 11362, Saudi Arabia
6 Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh, 12372, Saudi Arabia
7 Chitkara Centre for Research and Development, Chitkara University, Rajpura, 140401, India
8 Division of Research & Innovation, Uttaranchal University, Dehradun, 248007, India

* Corresponding Author: Shitharth Selvarajan. Email:

(This article belongs to the Special Issue: Advances in Object Detection: Methods and Applications)

Computers, Materials & Continua 2025, 84(2), 3541-3557. https://doi.org/10.32604/cmc.2025.064394

Received 14 February 2025; Accepted 04 June 2025; Issue published 03 July 2025

Abstract

This research investigates the application of digital images in military contexts by utilizing analytical equations to augment human visual capabilities. A comparable filter is used to improve the visual quality of the photographs by reducing truncations in the existing images. Furthermore, the collected images undergo processing using histogram gradients and a flexible threshold value that may be adjusted in specific situations. Thus, it is possible to reduce the occurrence of overlapping circumstances in collective picture characteristics by substituting grey-scale photos with colorized factors. The proposed method offers additional robust feature representations by imposing a limiting factor to reduce overall scattering values. This is achieved by visualizing a graphical function. Moreover, to derive valuable insights from a series of photos, both the separation and in-version processes are conducted. This involves analyzing comparison results across four different scenarios. The results of the comparative analysis show that the proposed method effectively reduces the difficulties associated with time and space to 1 s and 3%, respectively. In contrast, the existing strategy exhibits higher complexities of 3 s and 9.1%, respectively.

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Keywords

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