Underwater Image Enhancement Based on Removing Light Source Color and Dehazing

Abstract

Typical underwater images exhibit poor visibility because of light scattering and absorption in turbid water. To resolve the ill-posed problem, a novel underwater image enhancement method based on Removing Light Source Color and Dehazing(RLSCD) is proposed. Scene depth, which is assumed strongly correlated with attenuations, is often ignored in most of the previous methods. A new scene depth estimation, which takes the attenuations of the different light conditions into account, is first presented. Additionally, the background light is estimated based on gray open operation and scene depth to avoid that the pixels in the white objects and artificial lighting regions may be wrongly estimated as the background light. With the estimated background light and transmission map, the dehazed image is achievable. Moreover, the theoretical analysis of the Lambertian Model indicates that the disturbance of the light source color in dehazed image can be estimated, this phenomenon enables us to correct color distortion and light overcompensation by removing the disturbance. Experimental results demonstrate the RLSCD method outperforms state-of-theart methods in terms of relatively genuine color, increased contrast, and brightness. INDEX TERMSLight source color, Lambertian model, underwater image enhancement, gray open.

Automated fish cage net inspection using image processing techniques

“…Regarding the specific task of improving the lighting conditions using underwater image enhancement, there are state‐of‐the‐art methods that consider light diffusion properties and illumination irregularities along with trends of image restoration methodologies [18]. In our study, we neglect the effects of depth and focus on the poor contrast of images that may be caused by absorption and scattering since we are not considering deep ocean conditions in aquaculture.…”

“…More specifically, for improving contrast and sharpness, as well as for reducing non‐uniform lighting of the images we test a multiplicative imaging model and apply homomorphic filtering as a preprocessing step for improving contrast and sharpness, as well as for reducing non‐uniform lighting of the images [19]. Furthermore, to improve the lighting conditions we are currently experimenting with a LED source at the green–blue spectral region for reduced absorption and scattering [18]. Since the light transmission in underwater conditions does not form the main concept of this paper, we do not expand further on the formation and restoration of net images, but rather focus on the analysis of the net structure and its irregularities due to destructive damage.…”

Application of Locally Invariant Robust PCA for Underwater Image Recognition

“…In recent years, with the rapid development of artificial intelligence and machine learning, increased attention has been paid to underwater optical image recognition technology [1]. However, an underwater image in a real environment has unique attributes.…”

Single Underwater Image Restoration Based on Adaptive Transmission Fusion

“…Extended from the concept of the non-local haze-line in [22], this prior estimated the transmission for each pixel according to its distribution on a curve with a power function. Deng et al [23] introduced a removing light source color and dehazing (RLSCD) scheme to perform underwater image enhancement. The scene depth was estimated based on the attenuations of different light conditions and the background light was estimated based on gray open operations.…”

“…Illustration of the effectiveness of the background light estimation procedure, where B 1 , B 2 , and B are computed based on(23),(24), and (25), respectively.…”