The Research On Image Defogging And Image Enhancement

Nowadays fog is becoming a common weather because of pollution. The images of outdoor scenes obtained in fog usually have poor contrast and color fidelity. It must be difficult to estimate the objective using these blurred images, and it directly limited the outdoor vision systems. Therefore, in order to effectively improve the fog-degraded image quality, reduce the effect of the fog conditions to outdoor imaging system, there is practical and theoretical meaning of the images defogging and visibility Restoration fast and efficiently. The research contents of this dissertation are as followings:Firstly, we research on degradation mechanism of fog-image, image defogging algorithm in the non-model and model, especially on retinex algorithm and Image fusion technology. This paper proposes a image defogging algorithm based on the laplacian pyramid. The computing complexity in this algorithm is much lower than He’s algorithm, besides. This algorithm has better performance in image defogging,especially in dealing with the halo effect.Secondly, we research on color deviation of defogged image. Based on retinex algorithm, using guided image filtering to correct image color. The guided image filter can be used as an edge-preserving smoothing operator like the popular bilateral filter, but it has better behaviors near edges.Thirdly, we combine the above two algorithms. Using image defogging algorithm based on the laplacian pyramid to deal the image, and then using the guided image filtering to correct image color. Besides, we design experiments to comprehensively compare this method with others.