# Extraction of Independent Structural Images for Principal Component Thermography
## 1 Introduction  
Thermography is a well-established approach in the non-destructive analysis of materials. It is based on the study of temperature distribution (and evolution of such a distribution with time) on the surface of the sample of interest. In most cases, the term \"thermography\" refers to the so-called \"active\" thermographic approach. Active thermography assumes the study of those temperature distributions which are induced by application of an external thermal impact--in contrast to \"passive\" thermography which generally deals with objects which are heated by natural sources or by other heat sources which are not set up intentionally for experiment (e.g., sunlight or natural body heat) [1; 2; 3; 4]. This often makes the active thermography the only possible thermographic approach for the study of objects with no internal heat sources (e.g., composite and plastic panels for automotive applications). Active thermographic inspection (hereinafter thermography) requires two basic components: (a) thermal sensor and (b) the source of thermal impact (Figure 1). Although almost any thermal sensing device is applicable for use in thermographic experiments, modern thermography is generally performed with the use of thermal imagers (cameras). Thermal cameras allow one to obtain two-dimensional images showing the spatial distribution of temperature at the visible surface of the sample under analysis. Modern thermal cameras allow for the fast acquisition of such images, which creates possibilities for a large spectrum of potential experiments involving studies of how temperature distributions change with time (e.g., approaches of lock-in thermography, pulse phase thermography, etc.). The second component of a thermographic setup is the source of thermal influence. The primary function of this component is to bring the object of interest out of thermal equilibrium and initiate heat flows--and temperature re-distribution--in the sample. While the temperature is forced to change, the thermal sensor collects information on this variation, and necessary conclusions are made from this information either with or without additional processing. From the practical point of view, the source of thermal influence is usually the source of heat, among which the most widely used sources are heat guns, lasers, and powerful xenon flash lamps. The choice of the source is highly dependent on the nature of the sample to be studied (e.g., for metals it could be an induction heat source while for plastic parts induction heat is inapplicable). In the past few decades, thermography has found applications in numerous scientific fields and industries, paving the way from an exotic remote sensing method of warm objects to a quantitative method of non-destructive evaluation [5; 6]. Modern thermographic techniques utilize fast and high-precision devices for collection of data about surface thermal distribution. At the same time, advanced computational processing of collected data is utilized in many modern thermographic approaches for extraction of quantitative information on structure and integrity of studied objects. Among such techniques are well-known approaches of lock-in thermography (LT) [7; 8; 9; 10; 11; 12], pulse phase thermography (PPT) [11; 13; 14], thermal signal reconstruction (TSR) [11; 15; 16], and others. Most of these methods utilize various post-processing techniques in order to extract information regarding the structure and properties from the raw data on surface temperature distribution. This work is related to one particular approach in active thermography, in particular, the Principal Component Thermography (PCT) and a proposed method for enhancing the results collected with this technique. Unlike conventional PCT method, the proposed approach allows for obtaining images which represent individual structural features of the sample under analysis (e.g., defects, internal structure). Images extracted with the proposed algorithm are more straightforward and suitable for interpretation than Principal Component images.