1 research outputs found
An Image Based Technique for Enhancement of Underwater Images
The underwater images usually suffers from non-uniform lighting, low
contrast, blur and diminished colors. In this paper, we proposed an image based
preprocessing technique to enhance the quality of the underwater images. The
proposed technique comprises a combination of four filters such as homomorphic
filtering, wavelet denoising, bilateral filter and contrast equalization. These
filters are applied sequentially on degraded underwater images. The literature
survey reveals that image based preprocessing algorithms uses standard filter
techniques with various combinations. For smoothing the image, the image based
preprocessing algorithms uses the anisotropic filter. The main drawback of the
anisotropic filter is that iterative in nature and computation time is high
compared to bilateral filter. In the proposed technique, in addition to other
three filters, we employ a bilateral filter for smoothing the image. The
experimentation is carried out in two stages. In the first stage, we have
conducted various experiments on captured images and estimated optimal
parameters for bilateral filter. Similarly, optimal filter bank and optimal
wavelet shrinkage function are estimated for wavelet denoising. In the second
stage, we conducted the experiments using estimated optimal parameters, optimal
filter bank and optimal wavelet shrinkage function for evaluating the proposed
technique. We evaluated the technique using quantitative based criteria such as
a gradient magnitude histogram and Peak Signal to Noise Ratio (PSNR). Further,
the results are qualitatively evaluated based on edge detection results. The
proposed technique enhances the quality of the underwater images and can be
employed prior to apply computer vision techniques