Defogging is an essential preprocessing technique for object detection in computer vision-based systems and has been widely used in outdoor surveillance system applications. This paper proposes an efficient defogging algorithm for both static images and videos. Considering real-time applications, the proposed defogging algorithm involves a low-cost hardware oriented design that is based on an atmospheric scattering model and dark channel prior. Compared with previous low-complexity techniques, simulation results indicated that the proposed design demonstrated superior performance in terms of quantitative and qualitative evaluations. A weighting technique and a contour preserving estimation approach are adopted alternately to refine the factors in the defogging process. Furthermore, in the atmospheric light estimation, an adjuster is applied to the video for preventing 'flicker' which means that the brightness changes dramatically between two neighbor frames in the video. Hence, the proposed algorithm is suitable for video defogging applications, which have not been dealt with in previous approaches. To achieve the requirement of real-time applications for both static and dynamic images, an implementation of seven-stage very-large-scale integration architecture for the proposed algorithm is presented. By using TSMC 0.13- mu mathrm m technology, the design yielded a processing rate of approximately 200 Mpixels/s.
|Number of pages||14|
|Journal||IEEE Transactions on Circuits and Systems for Video Technology|
|Publication status||Published - 2019 Jan|
All Science Journal Classification (ASJC) codes
- Media Technology
- Electrical and Electronic Engineering