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The Codes of a Parallel Universe
#ArtDigital #CyberneticVision #Futuristic #SciFi #VirtualReality #AbstractArt #AI #AiArt #DigitalArt #Midjourney #DystopianDream #QuantumRealm #GlitchArt #LightFusion #NeuralNetwork
Les Codes d’un Univers Parallèle Explosion numérique d’énergie et de lumière, formant un vortex cybernétique aux nuances bleutées et dorées, évoquant un passage vers une autre dimension. Digital explosion of energy and light, forming a cybernetic vortex with blue and golden hues, evoking a gateway to another dimension.
January 30, 2025 at 12:16 PM
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SWIR-LightFusion: Multi-spectral Semantic Fusion of Synthetic SWIR with Thermal IR (LWIR/MWIR) and RGB

Muhammad Ishfaq Hussain, Ma Van Linh, Zubia Naz, Unse Fatima, Yeongmin Ko, Moongu Jeon

http://arxiv.org/abs/2510.13404
SWIR-LightFusion: Multi-spectral Semantic Fusion of Synthetic SWIR with Thermal IR (LWIR/MWIR) and RGB Muhammad Ishfaq Hussain, Ma Van Linh, Zubia Naz, Unse Fatima, Yeongmin Ko, Moongu Jeon http://arxiv.org/abs/2510.13404 Enhancing scene understanding in adverse visibility conditions remains a critical challenge for surveillance and autonomous navigation systems. Conventional imaging modalities, such as RGB and thermal infrared (MWIR / LWIR), when fused, often struggle to deliver comprehensive scene information, particularly under conditions of atmospheric interference or inadequate illumination. To address these limitations, Short-Wave Infrared (SWIR) imaging has emerged as a promising modality due to its ability to penetrate atmospheric disturbances and differentiate materials with improved clarity. However, the advancement and widespread implementation of SWIR-based systems face significant hurdles, primarily due to the scarcity of publicly accessible SWIR datasets. In response to this challenge, our research introduces an approach to synthetically generate SWIR-like structural/contrast cues (without claiming spectral reproduction) images from existing LWIR data using advanced contrast enhancement techniques. We then propose a multimodal fusion framework integrating synthetic SWIR, LWIR, and RGB modalities, employing an optimized encoder-decoder neural network architecture with modality-specific encoders and a softmax-gated fusion head. Comprehensive experiments on public RGB-LWIR benchmarks (M3FD, TNO, CAMEL, MSRS, RoadScene) and an additional private real RGB-MWIR-SWIR dataset demonstrate that our synthetic-SWIR-enhanced fusion framework improves fused-image quality (contrast, edge definition, structural fidelity) while maintaining real-time performance. We also add fair trimodal baselines (LP, LatLRR, GFF) and cascaded trimodal variants of U2Fusion/SwinFusion under a unified protocol. The outcomes highlight substantial potential for real-world applications
November 15, 2025 at 4:58 AM