IDE: Image Dehazing and Exposure Using an Enhanced Atmospheric Scattering Model.

Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:
Journal Article
Citation:
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, 2021, 30, pp. 2180-2192
Issue Date:
2021-01-26
Filename Description Size
IDE_final_submission.pdfAccepted manuscript18.47 MB
Adobe PDF
Full metadata record
Atmospheric scattering model (ASM) is one of the most widely used model to describe the imaging processing of hazy images. However, we found that ASM has an intrinsic limitation which leads to a dim effect in the recovered results. In this paper, by introducing a new parameter, i.e., light absorption coefficient, into ASM, an enhanced ASM (EASM) is attained, which can address the dim effect and better model outdoor hazy scenes. Relying on this EASM, a simple yet effective gray-world-assumption-based technique called IDE is then developed to enhance the visibility of hazy images. Experimental results show that IDE eliminates the dim effect and exhibits excellent dehazing performance. It is worth mentioning that IDE does not require any training process or extra information related to scene depth, which makes it very fast and robust. Moreover, the global stretch strategy used in IDE can effectively avoid some undesirable effects in recovery results, e.g., over-enhancement, over-saturation, and mist residue, etc. Comparison between the proposed IDE and other state-of-the-art techniques reveals the superiority of IDE in terms of both dehazing quality and efficiency over all the comparable techniques.
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