Light scattering and color change are two major sources of distortion for underwater photography. Light scattering is caused by light incident on objects reflected and deflected multiple times by particles present in the water before reaching the camera. This in turn lowers the visibility and contrast of the image captured. Color change corresponds to the varying degrees of attenuation encountered by light traveling in the water with different wavelengths, rendering ambient underwater environments dominated by a bluish tone. No existing underwater processing techniques can handle light scattering and color change distortions suffered by underwater images, and the possible presence of artificial lighting simultaneously. This paper proposes a novel systematic approach to enhance underwater images by a dehazing algorithm, to compensate the attenuation discrepancy along the propagation path, and to take the influence of the possible presence of an artifical light source into consideration. Once the depth map, i.e., distances between the objects and the camera, is estimated, the foreground and background within a scene are segmented. The light intensities of foreground and background are compared to determine whether an artificial light source is employed during the image capturing process. After compensating the effect of artifical light, the haze phenomenon and discrepancy in wavelength attenuation along the underwater propagation path to camera are corrected. Next, the water depth in the image scene is estimated according to the residual energy ratios of different color channels existing in the background light. Based on the amount of attenuation corresponding to each light wavelength, color change compensation is conducted to restore color balance. The performance of the proposed algorithm for wavelength compensation and image dehazing (WCID) is evaluated both objectively and subjectively by utilizing ground-truth color patches and video downloaded from the Youtube website. Both results demonstrate that images with significantly enhanced visibility and superior color fidelity are obtained by the WCID proposed.

Underwater Image Enhancement by Wavelength Compensation and Dehazing

Underwater images suffer from blurring effects, low contrast, and grayed out colors due to the absorption and scattering effects under the water. Many image enhancement algorithms for improving the visual quality of underwater images have been developed. Unfortunately, no well-accepted objective measure exists that can evaluate the quality of underwater images similar to human perception. Predominant underwater image processing algorithms use either a subjective evaluation, which is time consuming and biased, or a generic image quality measure, which fails to consider the properties of underwater images. To address this problem, a new nonreference underwater image quality measure (UIQM) is presented in this paper. The UIQM comprises three underwater image attribute measures: the underwater image colorfulness measure (UICM), the underwater image sharpness measure (UISM), and the underwater image contrast measure (UIConM). Each attribute is selected for evaluating one aspect of the underwater image degradation, and each presented attribute measure is inspired by the properties of human visual systems (HVSs). The experimental results demonstrate that the measures effectively evaluate the underwater image quality in accordance with the human perceptions. These measures are also used on the AirAsia 8501 wreckage images to show their importance in practical applications.

Human-Visual-System-Inspired Underwater Image Quality Measures

Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.

An Underwater Color Image Quality Evaluation Metric

The underwater image processing area has received considerable attention within the last decades, showing important achievements. In this paper we review some of the most recent methods that have been specifically developed for the underwater environment. These techniques are capable of extending the range of underwater imaging, improving image contrast and resolution. After considering the basic physics of the light propagation in the water medium, we focus on the different algorithms available in the literature. The conditions for which each of them have been originally developed are highlighted as well as the quality assessment methods used to evaluate their performance.

/pdf/underwater-image-processing-state-of-the-art-of-restoration-5bkw44ctbb.pdf

Underwater image processing: state of the art of restoration and image enhancement methods

Preface 1. Basic properties of radiation, atmospheres and oceans 2. Basic state variables 3. Interaction of radiation with matter 4. Formulation of radiative transfer problems 5. Approximate solutions of prototype problems 6. Accurate numerical solutions of prototype problems 7. Emission-dominated radiative processes 8. Radiative transfer in spectrally-complex media 9. Solar radiation driving photochemistry and photobiology 10. The role of radiation in climate Appendix 1. A primer on radiative transfer: absorption and scattering opacity Appendix 2. Stokes parameters, Poincare sphere, and the Mueller matrix Appendix 3. Nomenclature: glossary of symbols Appendix 4. Principle of reciprocity for the bidirectional reflectance Appendix 5. Isolation of the azimuth-dependence Appendix 6. The streaming term in spherical geometry Appendix 7. Reflectance and transmittance of the invariant intensity (I n2) Appendix 8. Scaling transformation for anisotropic scattering Appendix 9. Reciprocity, duality and effects of surface reflection Appendix 10. Removal of overflow problems in the intensity formulas.

Radiative Transfer in the Atmosphere and Ocean

Using a modified form of the anomalous diffraction approximation we have been able to derive in closed form an analytic expression for the phase function of Mie scatterers integrated over an inverse power law (Junge) size distribution. The analysis explains the apparent singularity seen experimentally at the forward scattering angle. Simple relationships are also derived that relate the inverse power law as a function of scattering angle in the near forward direction to the power law of the size distribution. The parameters of the formula are the relative index of refraction and the inverse power of the size distribution. A comparison is given between the analytic formula and exact integration of the Mie scattering for spheres. This new phase function is used in the analysis of forward angle transmissometer- nephelometer data collected by DREV in the Arctic, Atlantic, and Pacific.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Analytic phase function for ocean water

A careful analysis of a scattering and absorption database of the waters off the coasts of Canada shows that a laser-assisted camera system will have a significantly improved viewing performance over conventional systems. The laser underwater camera image enhancer system is a range-gated laser system that can be mounted on a remotely operated vehicle. The system uses a 2-kHz diode-pumped frequency-doubled Nd:YAG laser as an illumination source. The light is collected by a 10-cm-diam zoom lens. The detector is a gated image intensifier with a 7-ns gate and a gain that is continuously variable from 500 to 1,000,000. The system has been tested in a water tank facility at Defence Research Establishment Valcartier and has been mounted on the HYSUB 5000 remotely operated vehicle for sea trials. In the strongly scattering waters typical of harbor approaches, this system has a range of from three to five times that of a conventional camera with floodlights.

Range-gated underwater laser imaging system

The presented effort is aimed at establishing a framework in order to restore underwater imagery to the best possible level, working with both simulated and field measured data. Under this framework, the traditional image restoration approach is extended by incorporating underwater optical properties into the system response function, specifically the point spread function (PSF) in spatial domain and modulation transfer function (MTF) in frequency domain. Due to the intensity variations involved in underwater sensing, denoising is carefully carried out by wavelet decompositions. This is necessary to explore different effects of restoration constrains, and especially their response to underwater environment where the effects of scattering can be easily treated as either signal or noise. The images are then restored using measured or modeled PSFs. An objective image quality metric, tuned with environmental optical properties, is designed to gauge the effectiveness of the restoration, and serves to check the optimization approach. This metric utilizes previous wavelet decompositions to constrain the sharpness metric based on grayscale slopes at the edge, weighted by the ratio of the power of high frequency components of the image to the total power of the image. Modeled PSFs, based on Wells' small angle approximations, are compared to those derived from Monte Carlo simulation using measured scattering properties. Initial results are presented, including estimation of water optical properties from the imagery-derived MTFs, and optimization outputs applying automated restoration framework.

/pdf/automated-underwater-image-restoration-and-retrieval-of-tban7hk2lr.pdf

Automated underwater image restoration and retrieval of related optical properties

This chapter analyzes various aspects of the particle size distribution (PSD). PSD is one of the key parameters defining the interaction of light with natural waters and hence, has a paramount importance for the optics of natural waters. The PSD should be interpreted as a particle-size-dependent average number of particles of the given size in a volume of water. The size distribution is generally time dependent also in a more fundamental way because a particle population is subject to several competing processes that can remove and add particles as well as convert one type of particles into another. The equivalent spherical diameter has gained a considerable recognition in particle size analysis of water-borne particles because of the widely used electro resistance technique. It is found that the definition of the maximum information size grid depends strongly on the application or interest, which prompts the measurements. One application of the particle size transformation is the comparison or splicing of size distributions determined with different techniques for the same particle population. The uncertainty of the PSD measurements is also elaborated.

Chapter 5 – The particle size distribution

We present results from trials of the LUCIE 2 (Laser Underwater Camera Image Enhancer) conducted in Halifax Harbor, Nova Scotia, Canada and Esquimalt Harbor, Victoria, British Columbia, Canada. LUCIE 2 is a new compact laser range gated camera (10 inches in diameter, 24 inches in length, and neutrally buoyant in water) originally designed to improve search and recovery operations under eye safe restrictions. The flexibility and eye safety of this second generation LUCIE makes it a tool for improved hull searches and force protection operations when divers are in the water attempting to identify bottom lying objects. The camera is equipped with a full image geo-positioning system. To cover various environmental and targets size conditions, the gate-delay, gate width, polarization and viewing and illuminating angles can be varied as well. We present an analysis on the performance of the system in various water conditions using several target types and a comparison with diver and camera identification. Coincident in-situ optical properties of absorption and scattering were taken to help resolve the environmental information contained in the LUCIE image. Several new capabilities are currently being designed and tested, among them a differential polarization imaging system, a stabilized line of sight system with step-stare capability for high resolution mosaic area coverage, a precision dimensioning system and a diver guided and operated version.

Georges R. Fournier

Papers

Analytic phase function for ocean water

Range-gated underwater laser imaging system

Automated underwater image restoration and retrieval of related optical properties

Chapter 5 – The particle size distribution

In harbor underwater threat detection/identification using active imaging