An Efficient Fusion-Based Defogging

作者：Guo Jing Ming^*; Syue Jin Yu; Radzicki Vincent R; Lee Hua

来源：IEEE Transactions on Image Processing, 2017, 26(9): 4217-4228.

DOI：10.1109/TIP.2017.2706526

• Image enhancement
• defogging
• dehaze
• dark channel prior

Degradation in visibility is often introduced to images captured in poor weather conditions, such as fog or haze. To overcome this problem, conventional approaches focus mainly on the enhancement of the overall image contrast. However, because of the unspecified light-source distribution or unsuitable mathematical constraints of the cost functions, it is often difficult to achieve quality results. In this paper, a fusion-based transmission estimation method is introduced to adaptively combine two different transmission models. Specifically, the new fusion weighting scheme and the atmospheric light computed from the Gaussian-based dark channel method improve the estimation of the locations of the light sources. To reduce the flickering effect introduced during the process of frame-based dehazing, a flicker-free module is formulated to alleviate the impacts. The systematic assessments show that this approach is capable of achieving superior defogging and dehazing performance, compared with superior defogging and dehazing performance, compared with the state-of-the-art methods, both quantitatively and qualitatively.

• 出版日期2017-9