Model-based restoration of underwater spectral images captured with narrowband filters

Abstract

Underwater spectral imaging is a promising method for mapping, classification and health monitoring of coral reefs and seafloor inhabitants. However, the spectrum of light is distorted during the underwater imaging process due to wavelength-dependent attenuation by the water. This paper presents a model-based method that accurately restores brightness of underwater spectral images captured with narrowband filters. A model is built for narrowband underwater spectral imaging. The model structure is derived from physical principles, representing the absorption, scattering and refraction by water and the optical properties of narrowband filters, lenses and image sensors. The model coefficients are calibrated based on spectral images captured underwater and in air. With the imaging model available, energy loss due to water attenuation is restored for images captured at different underwater distances. An experimental setup is built and experiments are carried out to verify the proposed method. Underwater images captured within an underwater distance of 260 cm are restored and compared with those in air. Results show that the relative restoration error is 3.58% on average for the test images, thus proving the accuracy of the proposed method.

Underwater Hyperspectral Imaging Technology and Its Applications for Detecting and Mapping the Seafloor: A Review

“…Sørensen [ 55 ] simulated the reflectance from underwater objects by using the Oran-Nayar reflectance model, and simultaneously studied the influence of uneven illumination on the image classification accuracy through normalization and estimating reflectance approaches. Guo et al [ 56 ] presented a model for accurately restoring the brightness of underwater spectral images based on the underwater multispectral imager (UMI) with a filter wheel, and calibrated the model coefficients with spectral images captured underwater and in air. The refraction influence caused by the optical glass window in front of the camera was also considered in this model.…”

TuLUMIS - a tunable LED-based underwater multispectral imaging system

“…The spectral scanning method stacks up a sequence of monochrome images of the scene at different wavelengths specified by narrow-band filters in front of the sensor. In order to scan more wavelengths in less time, motorized filter wheels [25] and solid-state tunable filters (e.g., LCTF and AOTF [26]) have been introduced. Gleason et al studied coral reefs with a six-band filter wheel underwater multispectral camera, and concluded an improvement of using narrow spectral bands ratio combined with image texture measures in automated coral classification [27].…”

Visual detection and feature recognition of underwater target using a novel model-based method

“…6 Imaging is regarded as a promising method for detecting underwater environment, 7 and camera has been one indispensable sensor on underwater robotics. 8 Through the efforts of many scholars, underwater optics plays an important role in target recognition, map creation, underwater positioning, AUV homing and docking, 9 and many other fields.…”

“…The factor distorts the spectral energy distribution in underwater images as well as cause the images to be dark and hazy. 8,[12][13][14][15][16] Some research works have been done to remove the effects of water column on images. 17,18 Other researches are devoted to modeling of underwater imaging process, calibration of the optical properties of water, and correction of the underwater images.…”

“…17,18 Other researches are devoted to modeling of underwater imaging process, calibration of the optical properties of water, and correction of the underwater images. 8 The attenuation of light has been modeled using the Beer-Lambert law in most studies, [18][19][20][21] but various specific factors are considered in different models, for example, see the study by Guo et al 8 Another problem is feature recognition. A few of research have proposed a variety of target recognition systems and algorithms.…”