Photometric Calibration and Image Stitching for a Large Field of View Multi-Camera System

Abstract

A new compact large field of view (FOV) multi-camera system is introduced. The camera is based on seven tiny complementary metal-oxide-semiconductor sensor modules covering over 160° × 160° FOV. Although image stitching has been studied extensively, sensor and lens differences have not been considered in previous multi-camera devices. In this study, we have calibrated the photometric characteristics of the multi-camera device. Lenses were not mounted on the sensor in the process of radiometric response calibration to eliminate the influence of the focusing effect of uniform light from an integrating sphere. Linearity range of the radiometric response, non-linearity response characteristics, sensitivity, and dark current of the camera response function are presented. The R, G, and B channels have different responses for the same illuminance. Vignetting artifact patterns have been tested. The actual luminance of the object is retrieved by sensor calibration results, and is used to blend images to make panoramas reflect the objective luminance more objectively. This compensates for the limitation of stitching images that are more realistic only through the smoothing method. The dynamic range limitation of can be resolved by using multiple cameras that cover a large field of view instead of a single image sensor with a wide-angle lens. The dynamic range is expanded by 48-fold in this system. We can obtain seven images in one shot with this multi-camera system, at 13 frames per second.

Lookup Table Approach for Radiometric Calibration of Miniaturized Multispectral Camera Mounted on an Unmanned Aerial Vehicle

“…The reliability of the results was verified from two aspects: relative accuracy and absolute accuracy, and comparison with the calibration method provided by the manufacturer of the spectral camera. In earlier studies, only one of the verification approaches has been commonly used [14,24,42]. This limits the wide utilization of sensors.…”

Camera preparation and performance for 3D luminance mapping of road environments

“…However, a large, ideally uniform luminance source is more a theoretical than a practical device. Therefore, it is more pragmatic to solve the vignetting for example by using a small diameter luminance source in a set of locations within the camera's field of view or a large diameter luminance source with its exit port covering the camera's full field of view (Inanici, 2006;Cai and Chung, 2011;Lu et al, 2016;Mead and Mosalam, 2017). Alternatively, vignetting information can be extracted from a set of images or a single image by applying an algorithmic method (Goldman and Chen, 2005;Zheng et al, 2008;Kim and Pollefeys, 2008;Zheng et al, 2009).…”

Ams-3000 Large Field View Aerial Mapping System: Basic Principles and the Workflow

“…These aerial mapping cameras have solved part of the demand of the market to some extent, but they are still far from meeting the demand of China's rapid economic construction for a large amount of aerial remote sensing surveying and mapping geographic information. Therefore, it is very necessary to develop three-line array stereo airborne mapping cameras with high resolution and large field of view to meet the needs of mapping of large scales (Lu et al, 2016). Based on the above requirements, AMS-3000 camera system was developed.…”