STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Advancements in Robotics

Visionary Fusion: Empowering Robot Sight with Model-driven Multi-band Enhancement

  1. Ushaa Eswaran
  2. C. Pushpalatha
  3. Shaik Beebi
  4. B. Mallesh

Abstract

Single image enhancement is crucial for improving visual quality in applications like robot vision. This study proposes a novel topic-model assisted multi-band image fusion method to enhance a single input image while preserving semantic information. The key innovation is using topic models for adaptive band fusion based on image content. Comparative experiments on benchmark datasets demonstrate that the proposed technique outperforms state-of-the-art methods in quantitative and qualitative evaluation. This study also provides real-time demonstrations and case studies in robot navigation, highlighting the efficacy of the proposed fusion strategy. The fused images exhibit finer details and color consistency leading to improved navigation and obstacle avoidance. This technique has wide-ranging applications for computer vision related tasks in autonomous systems.

Keywords

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