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Turkish Journal of Electrical Engineering and Computer Sciences

DOI

10.3906/elk-1810-13

Abstract

Objects and their feature identification in hazy or foggy weather conditions has been of interest in the last decades. Improving image visualization by removing weather influence factors for easy image postprocessing, such as object detection, has benefits for human assistance systems. In this paper, we propose a novel variational model that will be capable of jointly segmenting and dehazing a given image. The proposed model incorporates atmospheric veil estimation and locally computed denoising constrained surfaces into a level set function by performing a robust and efficient image dehazing and segmentation scheme for both gray and color outdoor images. The proposed model not only shows efficient segmentation of objects in foggy images by outperforming state-of-the-art methods but also produces dehazed object results in the same time.

Keywords

Active contours, image dehazing, variational approach, segmentation, Euler--Lagrange equation

First Page

1652

Last Page

1666

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