Geometric calibration and radiometric correction of the maia multispectral camera

Multispectral imaging is a widely used remote sensing technique, whose applications range from agriculture to environmental monitoring, from food quality check to cultural heritage diagnostic. A variety of multispectral imaging sensors are available on the market, many of them designed to be mounted on different platform, especially small drones. This work focuses on the geometric and radiometric characterization of a brand-new, lightweight, low-cost multispectral camera, called MAIA. The MAIA camera is equipped with nine sensors, allowing for the acquisition of images in the visible and near infrared parts of the electromagnetic spectrum. Two versions are available, characterised by different set of band-pass filters, inspired by the sensors mounted on the WorlView-2 and Sentinel2 satellites, respectively. The camera details and the developed procedures for the geometric calibrations and radiometric correction are presented in the paper

OSPC: Online Sequential Photometric Calibration

Photometric calibration is essential to many computer vision applications. One of its key benefits is enhancing the performance of Visual SLAM, especially when it depends on a direct method for tracking, such as the standard KLT algorithm. Another advantage could be in retrieving the sensor irradiance values from measured intensities, as a pre-processing step for some vision algorithms, such as shape-from-shading. Current photometric calibration systems rely on a joint optimization problem and encounter an ambiguity in the estimates, which can only be resolved using ground truth information. We propose a novel method that solves for photometric parameters using a sequential estimation approach. Our proposed method achieves high accuracy in estimating all parameters; furthermore, the formulations are linear and convex, which makes the solution fast and suitable for online applications. Experiments on a Visual Odometry system validate the proposed method and demonstrate its advantages

The impact of spatial resolution on riparian leaf area index modelling using remote sensing

This thesis investigated the impact of differing sensor spatial resolutions on leaf area index (LAI) modelling. Airborne images along with ground measurements of LAI were acquired for riparian areas along the Oldman River in southern Alberta. Airborne images were spatially resampled to spatial resolutions between 18 cm and 500 m, and the Modified Simple Ratio (MSR) was calculated from the imagery. LAI regression models were created at each spatial resolution, and changes in the relationship between MSR and LAI were observed at each spatial resolution, as well as changes in the modelled LAI estimates. The relationship between MSR and LAI was scale invariant at spatial resolutions as low as 10 m, and only moderately changed until 30 m. MSR and predicted LAI gradually reduced as resolution coarsened further, with large changes occurred beyond 100 m. No relationship was evident between MSR and LAI at spatial resolutions coarser than 300 m

New Test Set for Video Quality Benchmarking

A new test set design and benchmarking approach (US Patent pending) allows a standard observer to assess the end-to-end image quality characteristics of video imaging systems operating in day time or low-light conditions. It uses randomized targets based on extensive application of Photometry, Geometrical Optics, and Digital Media. The benchmarking takes into account the target’s contrast sensitivity, its color characteristics, and several aspects of human vision such as visual acuity and dynamic response. The standard observer is part of the extended video imaging system (EVIS). The new test set allows image quality benchmarking by a panel of standard observers at the same time. The new approach shows that an unbiased assessment can be guaranteed. Manufacturers, system integrators, and end users will assess end-to-end performance by simulating a choice of different colors, luminance levels, and dynamic conditions in the laboratory or in permanent video systems installations