## 2 Methodology
### Data Collection and Pre-Processing
#### 2.2.1 Datasets  
The aim of this study is to evaluate face hallucination DL networks on images acquired in thermography, i.e., intensities of electromagnetic radiation in the range of 8-12 um (Long-Wave Infrared). In thermal imaging, electromagnetic radiation intensities are represented as digital values, usually of a 14-bit resolution. The final image is constructed by converting raw radiation values to temperature data by assigning color values to the digital ones.  
The SC3000 database is a collection of thermal sequences recorded for 40 volunteers from a group of 21 females and 19 males of the age \(34.11\pm 12\). For data acquisition the FLIR(r) SC3000 thermal camera was used. To record sequences, the camera was placed on a tripod at the height of 112 cm from the ground and at the distance of 1.2 m from a face of the volunteer. The sequences were gathered over a period of 2 min each, during which volunteers were asked to look directly into the camera and stay possibly still. The model of the camera used for data collection is capable of recording temperature in a range from \(-20\)\({}^{\circ}\)C to +80 \({}^{\circ}\)C in the 320 \(\times\) 240 pixels spatial resolution at 30 Frames Per Second (FPS). Data was captured in the noise reduction mode in the 14-bit radiometric format, which was then linearly down-scaled and saved as 8-bit grayscale PNG images, resulting in 3600 frames per person. In addition, to avoid contrast decrease by lossy data compression, we also generated 16-bit grayscale PNG images by up-scaling of the bit-depth to 16-bit float values (3600 frames per person). In order to obtain ground-truth measurements for respiratory rate, each volunteer was asked to bend the finger when exhaling air and to straighten it when inhaling in the way that it can be captured on the camera.  
The second dataset used in our research, refereed thereafter as the Lepton dataset, consists of 31 1-min thermal sequences obtained from volunteers of the age \(26\pm 8.1\). For data capture, the FLIR(r) Lepton thermal camera was used. Due to the small form factor of the device (a circuit board is smaller than 1 cm\({}^{2}\)), this camera module can be incorporated in embedded platforms, allowing for application in various medical oriented solutions [45; 46]. The Lepton camera is equipped with a thermal sensor capable of recording data in the 14-bit dynamic range and the 80 \(\times\) 60 spatial resolution at 9 FPS. Acquired sequences were up-sampled in the post-processing step to 12 FPS in order to increase the number of samples. These frames were further used for our model training and it's crucial to provide deep neural networks with enough data to make correct predictions [47]. During the data capture the camera was placed at a distance of 0.5 m from a volunteer's face. Similarly to the SC3000 dataset, obtained raw data were linearly down-scaled and saved as 8-bit grayscale PNG images, resulting in 720 frames per person. Also, to represent data in the PNG image format while avoiding loss of information, we generated a second set of images (720 frames per person) with values represented as 16-bit float numbers. The reference respiratory rate measurements were collected using the respiratory monitor belt (Vernier RMB), which strapped around the chest can record the pressure associated with the expansion and contraction of the chest during breathing.  
Both datasets were captured in a laboratory room at the ambient temperature of 23 to 27 \({}^{\circ}\)C. Every participant, who took part in the data collection process, was informed about the details of the experiment and the signed informed consent was obtained from each volunteer. The experiments were performed with agreements to rules specified by the regional, institutional Bioethical Commission.