Emerging Trends and Challenges in Image Processing and Computer Vision for Agriculture: A Multidisciplinary Review

👥 Monika Vishwakarma, Rachana Dubey

📙 Abstract : Advances in image processing and computer vision have significantly enabled the shift from traditional large-area farming to data-driven, ultra-precision agriculture. Crop monitoring, disease detection, yield forecasting, and sustainable resource management in agricultural fields will require deep learning, edge computing, and multimodal sensing-powered visual intelligence systems by 2026. This multidisciplinary review paper provides a comprehensive synthesis of recent breakthroughs as well as long-standing challenges in image processing and computer vision in agriculture. Key advances include those investigated in edge-to-cloud architectures, multimodal data fusion, convolutional and transformer-based models, and vegetation indices. This complete review paper highlights ongoing challenges with data robustness and real-world applications, particularly for aquatic crops and this review paper concludes by outlining future research directions and provides valuable insights for researchers in the field of smart agriculture.

🔖 Keywords :️ Image Processing, Computer Vision, Precision Agriculture, Vision Transformers, Multimodal Fusion, Edge Computing, AIoT, Sustainable Farming.