Image Defogging Algorithm Based on Sparse Representation

Image Defogging Algorithm Based on Sparse Representation

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Aiming at the problems of low contrast and low definition of fog degraded image, this paper proposes an image defogging algorithm based on sparse representation.Firstly, the algorithm transforms image from RGB space to HSI space and uses two-level wavelet transform extract puffy spa headband features of image brightness components.Then, it uses the K-SVD algorithm training dictionary and learns the sparse features of the fog-free image to reconstructed I-components of the fog image.Using the nonlinear stretching approach for saturation component improves the brightness of the image.Finally, convert from HSI space to RGB berkley power worm 100 pack color space to get the defog image.

Experimental results show that the algorithm can effectively improve the contrast and visual effect of the image.Compared with several common defog algorithms, the percentage of image saturation pixels is better than the comparison algorithm.