Thermal Infrared Video Stabilization for Aerial Monitoring of Active Wildfires

Abstract

Measuring wildland fire behaviour is essential for fire science and fire management. Aerial thermal infrared (TIR) imaging provides outstanding opportunities to acquire such information remotely. Variables such as fire rate of spread (ROS), fire radiative power (FRP) and fire line intensity may be measured explicitly both in time and space, providing the necessary data to study the response of fire behaviour to weather, vegetation, topography and firefighting efforts. However, raw TIR imagery acquired by Unmanned Aerial Vehicles (UAVs) requires stabilization and georeferencing before any other processing can be performed. Aerial video usually suffers from instabilities produced by sensor movement. This problem is especially acute near an active wildfire due to fire-generated turbulence. Furthermore, the nature of fire TIR video presents some specific challenges that hinder robust inter-frame registration. Therefore, this paper presents a software-based video stabilization algorithm specifically designed for thermal infrared imagery of forest fires. After a comparative analysis of existing image registration algorithms, the KAZE feature-matching method was selected and accompanied by pre-and post-processing modules. These included foreground histogram equalization and a multireference framework designed to increase the algorithm's robustness in the presence of missing or faulty frames. Performance of the proposed algorithm was validated in a total of nine video sequences acquired during field fire experiments. The proposed algorithm yielded a registration accuracy between 10 and 1000 times higher than other tested methods, returned 10x more meaningful feature matches and proved robust in the presence of faulty video frames. The ability to automatically cancel camera movement for every frame in a video sequence solves a key limitation in data processing pipelines and opens the door to a number of systematic fire behaviour experimental analyses. Moreover, a completely automated process supports the development of decision support tools that can operate in real time during an emergency.

Orthorectification of Helicopter-Borne High Resolution Experimental Burn Observation from Infra Red Handheld Imagers

“…This matrix completes the warping between planar surfaces, yielding I rec If I m is changed too frequently, it may introduce unwanted drift resulting from the moving feature stabilization. This is probably the reason why the methodology of [28] is showing drift, as stabilization is performed on consecutive images (m = p − 1). Inversely, if I m is updated too slowly, image differences resulting from the fire evolution or from the view angle changes would degrade the alignment performance.…”

“…The development of a methodology to perform orthorectification (step a) to a large number of IR fire images collected from a moving platform and at a high frequency is a current need of the fire science community [23]. A recent work [28] proposed a first attempt to stabilize (image-to-image registration) a time series of IR images. However, the proposed methodology has some limitations since it only features good performance for images recorded from a stable vantage point (see drift in all footage of the Supplementary Material of [28]).…”

“…A recent work [28] proposed a first attempt to stabilize (image-to-image registration) a time series of IR images. However, the proposed methodology has some limitations since it only features good performance for images recorded from a stable vantage point (see drift in all footage of the Supplementary Material of [28]).…”

Thermal Characteristics and Integration Mechanism of Infrared Thermal Imaging (ITI) Solar and Coal-fired Complementary Power Stations

“…(2) The complementary method of replacing the feed water heater with the collector field [9][10], this complementary method is the most common in the solar-coal complementary system today. Depending on the size of the unit, the collector field replaces the feed water heater.…”

“…(3) Specific heat consumption of steam turbine: (4) Absolute internal efficiency of steam turbine: (5) Absolute electrical efficiency of steam turbine: (6) Turbine heat consumption rate: (7) Turbine steam consumption rate: (8) Calculation of thermal efficiency of the whole plant: (9) Standard coal consumption rate for power generation, g/(kW•h): (10) Heat consumption rate of the whole plant, kJ/(kW•h): According to the parameters of the regenerative system of the original coal-fired power station, the data is substituted into the relevant formula, and the thermal performance index of the unit under each working condition can be obtained from the calculation, as shown in Table 1.…”