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UNDERWATER IMAGE ENHANCEMENT

PRESENTED BY ARCHANA S S7 ECE ROLL NO 04 VKCET PARRIPALLY

UNDERWATER IMAGE ENHANCEMENT WAVELENGTH COMPENSATION AND DE-HAZING (WCID)

INTRODUCTIONSources of underwater image distortion are

1. Light Scattering2. Color Change

Light scattering lowers the visibility and contrast of captured image.

Color change leads to the varying degrees of attenuation.

Fig Hazing and bluish effect caused by light scattering and color change in underwater images.

To enhance the underwater image Wavelength compensation and dehazing algorithm is most appropriate(WCID).

Enhanced visibility and superior color fidelity can be obtained by WCID algorithm.

Image dehazing helps to restore clarity of underwater images.

WHAT IS HAZE?Haze is caused by suspended particles such as

sand, minerals in lakes, river and oceans.

Capturing image underwater is challenging due to haze caused by light.

Water surface effect

Underwater image formation model

FLOWCHART

UNDER WATER MODELUsing hazy image formation model, image formed at camera can be given as:

X = point in underwater scene,

= image captured by camera

= scene radiance at point x.= residual energy ratio.

= homogeneous background light

Residual energy ration can be given as:

Distance between camera and object: d(x)

• Haze increases with distance; so, haze can be useful to determine d(x).

• Using single image haze removal and dark channel prior d(x) can be determined-

Removal of artificial light source L

• Artificial lights are often supplemented to avoid insufficient lighting in underwater image

• Artificial light source can be detected by comparing luminance difference of foreground and the background.

Illuminated by an artificial light source, foreground appears brighter than background

Artificial light is not removed ,an overexposed image is obtained after compensation stage

Image obtained after eliminating haze, light scattering and color change .

Underwater image obtained after processing with WCID

Image obtained after processing with (a)WCID (b) dark-channel based Dehazing (c) chromatism-based dehazing (d) histogram qualization

RESULT

Quantitative performance evaluation (SNR values )

ADVANTAGES

• WCID results in superior haze removal and color balancing capabilities over dehazing and histogram equalization.

• Highest SNR values are obtained.

• Performance of WCID is most robust through different water depths.

References• John Y.Chinag and Ying-Ching Chen, “Underwater image enhancement by

wavelength compensation and dehazing,”IEEE transaction on image processing, vol.21,no.4,April 2012.

• K. He, J. Sun, and X. Tang, “Single image haze removal using DarkChannel Prior,” in Proc. IEEE CVPR, vol. 33, no.12,Dec.2011.

• K. Lebart, C. Smith, E. Trucco, and D. M. Lane, “Automatic indexing of underwater survey video: algorithm and benchmarking method,” IEEE J. Ocean. Eng., vol. 28, no. 4, pp. 673–686, Oct. 2003.

• Y. Y. Schechner and N. Karpel, “Recovery of underwater visibility and structure by polarization analysis,” IEEE J. Ocean. Eng., vol. 30, no. 3, pp. 570–587, Jul. 2005.