Stereoscopic imaging through the sea surface: I. Theory and error analysis

Abstract

The detection and recognition of submerged objects via airborne or spaceborne imaging platforms can be problematic, due to distortions resulting from refraction at the sea surface as well as absorption and scattering in atmospheric and aqueous media. In previous research, we showed that, given point-to-point measurement of interfacial topography and estimates of media optical parameters, it is often possible to partially invert refractive effects and compensate for first-order optical effects such as absorption and single scattering, thereby producing a visually acceptable, image-based reconstruction of a submerged target. Additionally, information concerning target depth or surface topography is obtained.Although potentially useful for human-in-the loop viewing scenarios, this method is not universally applicable to automated target recognition (ATR) due to reconstruction errors that tend to cluster in regions of detail.In this paper, we present theory and error analysis pertaining to stereoscopic viewing through a corrugated refractive interface and scattering media. Via stereoscopic imaging, one can produce a stereo pair image from which target depth and salient features can be extracted mathematically. Estimation of errors involved in this process is facilitated by partial knowledge of interfacial topography and is further enhanced by knowledge of media optical parameters. Analyses emphasize effects of sea state, topography estimation error, media optical parameters, and submergence depth. Reconstruction algorithm complexity is discussed in terms of work requirement applicable to sequential workstations and parallel computers.

<title>Reconstruction of submerged targets from multiple airborne images: II. Algorithms and simulation results</title>

“…These developments are based on previously theory and thus extend published research in multi-looking imaging [1][2][3][12][13][14] and trans-MBL image restoration [7][8][9]. The aforementioned models are applied to simulate trans-MBL imagery acquired under a variety of sea states and media turbidity conditions.…”

“…The integration process is designed to support semi-automatic derivation of a solid model that portrays an imaged target or scene. This approach is advantageous for target and feature location, especially in the presence of partial obscuration due to turbid optical media, overlying cover, or occlusion by other target objects.In previous research, we have analyzed the application of MU techniques to airborne imaging of surface and underwater targets [1][2][3]. Part 1 of this series of two papers contains error analysis of imaging through the sea surface (also called trans-MBL imaging, for Marine Boundary Layer).…”

“…In previous research, we have analyzed the application of MU techniques to airborne imaging of surface and underwater targets [1][2][3]. Part 1 of this series of two papers contains error analysis of imaging through the sea surface (also called trans-MBL imaging, for Marine Boundary Layer).…”