An Efficient Underwater Image Restoration Model for Digital Image Processing

Title

An Efficient Underwater Image Restoration Model for Digital Image Processing

Creator

Jacob J.J.; Savitha S.; Mukherjee D.

Description

Digital image processing (DIP) is showing a massive growth intodays trending world particularly, in the field of biological research. Underwater image analysis plays a vital role, where the images are easily prone to attenuation and haziness. Capturing underwater images has always been a challenging job due to dispersion and scattering of light inside water on a high scale. Several image enhancement and restoration methodologies are currently available to address these issues, where hazing and color diffusion are viewed as a common phenomenon in it. Such procedures normally includes two basic methodologies in it, namely dehazing and contrast or color enhancement, which improves the overall output of the degraded image. However, the quality and processing time of the images can still be enhanced with additional techniques incorporated to it. This work is intended toward proposing one such channel called improvised bright channel prior for dehazing the underwater images. The technique further improves on the existing methodologies by estimating the atmospheric light and refining the transmittance of the image along with image restoration. The experimental results show that the improvised bright channel prior methodology is found to perform better in dehazing underwater images with a balanced intensity in terms of dark and white patches obtained from it. When comparing and contrasting the processing time of the proposed methodology with the existing techniques, it is found that improvised bright channel prior performs better. Also, the quality of the dehazed underwater image obtained from the proposed channel is found to be effective when compared with the existing channels. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-401, pp. 95-107.

Date

2023-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Atmospheric light; Dehazing; Digital image processing; Improved bright channel prior; Transmittance image; Underwater image restoration

Coverage

Jacob J.J., Department of Computer Science and Engineering, Christ University, Karnataka, Bangalore, India; Savitha S., Department of Computer Science and Engineering, Christ University, Karnataka, Bangalore, India; Mukherjee D., Department of Computer Science and Engineering, Christ University, Karnataka, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981190097-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-19-0098-3_11

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132969781&doi=10.1007%2f978-981-19-0098-3_11&partnerID=40&md5=18a83089832a958416cd18e031f334d9