Model based image restoration for underwater images

Abstract

The inspection of offshore parks, dam walls and other infrastructure under water is expensive and time consuming, because such constructions must be inspected manually by divers. Underwater buildings have to be examined visually to find small cracks, spallings or other deficiencies. Automation of underwater inspection depends on established water-proved imaging systems. Most underwater imaging systems are based on acoustic sensors (sonar). The disadvantage of such an acoustic system is the loss of the complete visual impression. All information embedded in texture and surface reflectance gets lost. Therefore acoustic sensors are mostly insufficient for these kind of visual inspection tasks. Imaging systems based on optical sensors feature an enormous potential for underwater applications. The bandwidth from visual imaging systems reach from inspection of underwater buildings via marine biological applications through to exploration of the seafloor. The reason for the lack of established optical systems for underwater inspection tasks lies in technical difficulties of underwater image acquisition and processing. Lightening, highly degraded images make a computational postprocessing absolutely essential

Deriving inherent optical properties from background color and underwater image enhancement

“…We also compare the proposed method with the other two state of the art underwater image enhancement or restoration methods based on Dark Channel Prior, which are Chiang's method of wavelength compensation and image dehazing (WCID) (Chiang and Chen, 2012) and Stephan's method of model based image restoration (Stephan et al, 2013). The results are shown in Fig.…”

“…Many methods of underwater image enhancement techniques have been proposed and demonstrated in the last few years. Methods based polarization (Schechner and Karpel, 2004), chromatism (Carlevaris-Bianco et al, 2010), quaternions (Petit et al, 2009), color model (Iqbal et al, 2007), wavelength compensation and image dehazing (WCID) (Chiang and Chen, 2012), model based image restoration (Stephan et al, 2013) and so on, have been proved to be effective for underwater image enhancement. However, strong hypothesis, optical properties given specifically or measured in situ, and two or more images were usually used during the process of these image enhancement.…”

A novel underwater dam crack detection and classification approach based on sonar images

“…However, some of these methods are expensive, and others are neither sufficiently convenient nor reliable. Recently, detecting underwater dam cracks using sonar images has become one of the most important methods because it is nondestructive, intuitive, convenient and efficient [ 8 ].…”

A detection and classification approach for underwater dam cracks

“…8 Recently, underwater dam crack detection based on visible image processing technology has become one of the most important methods. 9 The visible image processing technology is convenient, intuitive, efficient, economical and nondestructive, which can meet the requirements of the dam crack detection. 10 However, there are some problems that need to be solved in underwater dam crack detection and classification based on visible images.…”