A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super-Resolution.

This paper presents a transfer domain strategy to tackle the limitations of low-resolution thermal sensors and generate higher-resolution images of reasonable quality. The proposed technique employs a CycleGAN architecture and uses a ResNet as an encoder in the generator along with an attention module and a novel loss function. The network is trained on a multi-resolution thermal image dataset acquired with three different thermal sensors.

Wide-Band Color Imagery Restoration for RGB-NIR Single Sensor Images.

Multi-spectral RGB-NIR sensors have become ubiquitous in recent years. These sensors allow the visible and near-infrared spectral bands of a given scene to be captured at the same time. With such cameras, the acquired imagery has a compromised RGB color representation due to near-infrared bands (700⁻1100 nm) cross-talking with the visible bands (400⁻700 nm).

Automatic association of chats and video tracks for activity learning and recognition in aerial video surveillance.

We describe two advanced video analysis techniques, including video-indexed by voice annotations (VIVA) and multi-media indexing and explorer (MINER). VIVA utilizes analyst call-outs (ACOs) in the form of chat messages (voice-to-text) to associate labels with video target tracks, to designate spatial-temporal activity boundaries and to augment video tracking in challenging scenarios. Challenging scenarios include low-resolution sensors, moving targets and target trajectories obscured by natural and man-made clutter.