Visual Enhancement of Underwater Images Using Transmission Estimation and Multi-Scale Fusion

Abstract

The demand for the exploration of ocean resources is increasing exponentially. Underwater image data plays a significant role in many research areas. Despite this, the visual quality of underwater images is degraded because of two main factors namely, backscattering and attenuation. Therefore, visual enhancement has become an essential process to recover the required data from the images. Many algorithms had been proposed in a decade for improving the quality of images. This paper aims to propose a single image enhancement technique without the use of any external datasets. For that, the degraded images are subjected to two main processes namely, color correction and image fusion. Initially, veiling light and transmission light is estimated to find the color required for correction. Veiling light refers to unwanted light, whereas transmission light refers to the required light for color correction. These estimated outputs are applied in the scene recovery equation. The image obtained from color correction is subjected to a fusion process where the image is categorized into two versions and applied to white balance and contrast enhancement techniques. The resultants are divided into three weight maps namely, luminance, saliency, chromaticity and fused using the Laplacian pyramid. The results obtained are graphically compared with their input data using RGB Histogram plot. Finally, image quality is measured and tabulated using underwater image quality measures.