Infrared (IR) imaging systems have sensor and optical limitations that result in degraded imagery. Apart from imperfect optics and the finite detector size being responsible for introducing blurring and aliasing, the detector fixed-pattern noise also adds a significant layer of degradation in the collected imagery. Here, we propose a single-shot super-resolution method that compensates for the nonuniformity noise of long-wave IR imaging systems. The strategy combines wavefront modulation and a reconstruction methodology based on total variation and nonlocal means regularizers to recover high-spatial frequencies while reducing noise. In simulations and experiments, we demonstrate a clear improvement of up to 16× in image resolution while significantly decreasing the fixed-pattern noise in the reconstructed images.
In this work, mid wavelength infrared microscopy imaging videos of several index finger pads, from voluntary people, are recorded to obtain their thermoregulation curves. The proposed non-invasive technique is able to capture spatial and temporal thermal information emitted from blood vessels under-skin, and the irrigation finger pad system, making possible to capture features that a visual-spectrum microscopy cannot detect. Using an infrared laboratory prepared method several voluntary patients exposed theirs fingers to thermal stress while the infrared data is recorded. Using standard infrared imaging and signal processing techniques the thermoregulation curves are estimated. The Cold/Hot Stress experiments have shown infrared data with exponential trend curves, with different recovering slopes for each voluntary person, and sometimes with two steps increasing slope in one person thermoregulation curve response.
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