Image Processing and Sparse Resolution for Underwater Imaging

Xiao Dan Sun; Zhuo Zhang; Xue Wu Zhang

doi:10.4028/www.scientific.net/AMM.599-601.1544

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 599-601Image Processing and Sparse Resolution for...

Image Processing and Sparse Resolution for Underwater Imaging

Abstract:

Super-resolution is useful for weak-target image reconstruction. The technique, however, is not yet suitable for underwater imaging implementation due to the complexity of underwater environment. In this paper, an image processing and sparse super-resolution is proposed to make it more suitable for underwater images. In this paper, image processing and image super-resolution are combined. It firstly used histogram equalization to increase local gray value and extent the gray value range to mate the details of the image texture range more distinct. By this we can raise the attention of the human eyes; then use Canny edge enhancement operator to make the edge of the image more clear; finally, by combining classical underwater point spread function (PSF) and the semi image blind restoration method, the image quality are further improved. The experimental results showed that the image recovered by this method had shaper edge and clearer textures.

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Periodical:

Applied Mechanics and Materials (Volumes 599-601)

Pages:

1544-1547

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.599-601.1544

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Online since:

August 2014

Authors:

Xiao Dan Sun*, Zhuo Zhang, Xue Wu Zhang

Keywords:

Histogram Equalization, Image Processing, Semi-Blind Image Restoration, Super-Resolution, Underwater Imaging

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