## 1 Introduction  
The early identification, localization and quantification of gas leaks is important from various points of view, such as health, safety or environmental aspects. Legal and economic considerations also play a role in ensuring the safety of industrial processes and products. Highly sensitive, handheld gas sensors are often used to detect leaks. However, these systems often require local sampling, which can be a time-consuming, error-prone manual task or risky in terms of toxic or explosive gases. For rapid monitoring, a remote gas detection solution without sampling is preferred. Optical and, in particular, laser-optical measurement methods in the near- and mid-infrared (NIR and MIR) are often well suited for determining gas concentrations [1; 2; 3; 4]. Another great wish for many applications (e.g., leak detection) is the visualization of invisible molecular species as an image or video. Since many gases show an infrared (IR) activity [5; 6], IR imaging can be used to visualize (invisible) molecular species. Well established, optical gas imaging (OGI) cameras can be described by a thermal camera modified by an optical bandpass filter in front of the quantum detector. The detector and IR filter are cooled to cryogenic temperatures around 77 K to increase the sensitivity (thermal noise reduction). The concept is based on the identification of thermal radiation differences between the target gas and the background. The difference is generated by gas absorption or emission, but only gases are detected that show MIR activity in the wavelength range of the bandpass filter. Since the spectral width of these filters is around 100 cm\({}^{-1}\) and more (larger than 3 THz), these passive OGI systems only provide a certain selectivity in terms of molecular species. A typical absorption line has a spectral width (full-width half-maximum, FWHM) around 0.1 cm\({}^{-1}\) (or 3 GHz). In consequence, any molecular lines absorbing within the range of the optical filter will be detected in an indistinguishable way, and an accurate gas concentration image is practically not feasible. This particularly holds for small molecules that show discrete absorption lines in contrast to larger molecules where the absorption lines form a broad and continuous absorption feature. These passive OGI concepts are well suited to identify comparably large natural gas leaks [7; 8; 9; 10; 11]. More powerful tools for spectroscopic imaging in terms of the selectivity and accuracy of gas concentration estimations (typically in units of ppm*m) have recently been demonstrated by active OGI concepts. In this context, active means the use of a specific illumination source. In these experiments, artificial gas leaks or releases have been illuminated by a tunable laser [12] and optical frequency combs [13] in the infrared wavelength range. The diffusely reflected or backscattered radiation has been detected by an IR camera. Tunable laser spectroscopy (TLS) imaging was used to demonstrate the detection of methane leakage at a leakage rate of a few milliliters per minute. In this case, the methane concentration images at frame rates up to 125 Hz were extracted by only two wavelengths [14]. Furthermore, the real-time capability [15] and quantitative leak rate determination via a deep learning approach [16] were demonstrated. However, the gas concentration images are based on a simple TLS modulation concept by modulating the laser wavelength on and off the gas absorption feature (two wavelengths) for each alternate frame. A higher spectral resolution (around 30 wavelengths) to resolve the narrow absorption lines of gases has been shown by dual-comb hyperspectral imaging at a frame rate of 10 Hz [17]. In this work, we aimed to investigate a TLS variant including a greater amount of spectral information from a specific methane absorption around 3271 nm compared to the two-wavelength approach described above. Traditionally, there are two main variants of TLS: wavelength modulation spectroscopy (WMS) and direct absorption spectroscopy (DAS) [18; 19].