Using XEVA video sensors in acquiring spectral reflectance coefficients

Abstract

The rapid and accurate detection and identification of water pollutants play an enormous role is preserving water ecosystems and protecting the surrounding environment. Such detection and identification are usually conducted in situ, using traditional measurement methods. These methods however are very time consuming and costly especially when conducting them on a large scale. A team of specialists from the Department of Remote Sensing and Photogrammetry from the Military University of Technology in Warsaw have been taking part in a project entitled "IRAMSWater-Innovative remote sensing system for the monitoring of pollutants in rivers, offshore waters and flooded areas" (PBS1/B9/8/2012) financed by the polish National Centre for Research and Development. Its main aim is the creation of a remote sensing system based on hyperspectral sensors which will enable the evaluation, detection and distribution of biological, physical and chemical pollutants in the examined waters in real time. These analyses will be conducted based on spectral characteristics of a wide selection of pollutants. In order to acquire these spectral characteristics in a precise manner from hyperspectral data, the research team was required to establish a precise methodology for obtaining these data. The most common approach is to acquire the imagery first, ensuring that each scene contains at least one reference panel with a well know spectral characteristic, and then transforming the imagery and calculating the spectral response curves during post-processing. The IRAMSWater team had proposed a method of extracting precise reflectance coefficients in quasi real time without the need for using a reference panel on the scene. This is done by precisely determining the camera exposure parameters in laboratory conditions. The article presents laboratory experiments conducted using two XEVA video sensors (400-1700 nm spectral data registration), which allowed the authors to form a methodology for acquiring spectral reflectance coefficients of objects within a scene without the need for a reference panel.

Evaluating sensor linearity of chosen infrared sensors

“…The results of these experiments had been described in more detail in "Using XEVA video sensors in acquiring spectral reflectance coefficients", Walczykowski et al, 2014. However, when conducting the same measurements using the second sensor, the XEVA XS-1.7.320, these accuracies were much lower during some, not all, conducted experiments.…”

Examining the possibility of correcting imagery acquired for the purpose of obtaining spectral reflectance coefficients in the infrared range using photometric measurements

“…The developed methodology gave very good results, the repeatability of which was within 1-2%. These results had been presented in detail by Walczykowski et al 2014. The next step was to alter the lighting conditions of the scene.…”

“…The methodology is based on the concept, that if a sensor has fixed exposure parameters (f-stop and exposure/integration time) and used to acquire imagery in stable lighting conditions, the sensor response will always be the same within a small margin of error resulting from the system's SNR (Walczykowski et al, 2014). If we however increase the exposure time twofold, the sensors response (DN value) will also increase by the same factor.…”

Pre-processing of Xeva-XS imagery for determining spectral reflectance coefficients in laboratory conditions

“…There are two different methodologies which can be used to acquire imagery from which it would be possible to obtain spectral reflectance characteristics -the first based on images of a scene in which a reference panel had been included (i.e. Peddle et al, 2001;Thome, 2001;Schaepman, 2007;Milton et al, 2009;Kopackova et al, 2014), and the second based on precisely selected exposure parameters (Walczykowski et al, 2014). This paper is concerned with the first of these two methods based on experiments conducted using a 14bit XEVA XS-1.7.320 infrared sensor.…”