Abstract
This paper presents a fast and compact hardware implementation using an efficient haze removal algorithm. The algorithm employs a modified hybrid median filter to estimate the hazy particle map, which is subsequently subtracted from the hazy image to recover the haze-free image. Adaptive tone remapping is also used to improve the narrow dynamic range due to haze removal. The computation error of the proposed hardware architecture is minimized compared with the floating-point algorithm. To ensure real-time hardware operation, the proposed architecture utilizes the modified hybrid median filter using the well-known Batcher’s parallel sort. Hardware verification confirmed that high-resolution video standards were processed in real time for haze removal.
Highlights
With the development of self-driving vehicles and intelligent monitoring systems, there is a growing demand for haze removal algorithms [1,2,3]
The haze removal algorithms can be roughly divided into two main categories: multiple image processing [4,5] and single image processing [6,7,8,9,10,11,12,13,14,15,16,17]
All the algorithms mentioned above require multiple frame memories, which greatly increase the hardware complexity at a high cost in the hardware implementation phase. Another approach proposed by Kim et al removed haze from hazy images using hazy particle maps, estimated via modified hybrid median filter [11]
Summary
With the development of self-driving vehicles and intelligent monitoring systems, there is a growing demand for haze removal algorithms [1,2,3]. All the algorithms mentioned above require multiple frame memories, which greatly increase the hardware complexity at a high cost in the hardware implementation phase Another approach proposed by Kim et al removed haze from hazy images using hazy particle maps, estimated via modified hybrid median filter (mHMF) [11]. This paper presents a 4K-capable hardware design using Kim et al.’s algorithm that meets the real-time processing criteria and does not require frame storage memory for consecutive images (or video frames) with high similarity.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
