VLSI Implementation for an Adaptive Haze Removal Method

Abstract

In bad weather conditions such as fog or haze the visibility of an image taken under such circumstances would be severely blurred This is often the case for dashboard camera recording on freeways recordings taken by security cameras in the morning if mountain areas video evidence taken by coastguards etc Objects in this blurred images and recordings are oftentimes hard to distinguish which makes it unsuitable to analyzing Therefore to find a method that recovers a clear image form a foggy one is a very important issue Recently various defogging techniques were proposed to process static images but only a few of theses were suitable for VLSI design or real-time applications Hence the goal of this thesis is to propose an efficient video defogging method with low complexity that is suitable for VLSI circuit implementation The proposed method has three characteristics: First estimating the global atmospheric light by dark channel prior and computing the local atmospheric light according to visibility of patch Second using an edge detection to ease the halo effect Third calculating the atmospheric light and the recovered images at the same time exploiting temporal dependency to increase the processing rate The experiment results show by comparing the recovered images of our method with other hardware implementation methods that the former was more efficiently and delivered images at a higher quality The hardware architecture of the proposed design was implemented by Verilog and Synopsys Design Compiler was used to synthesis the design with the TSMC 130nm cell library The synthesis result showed that the proposed design contains 18 6K gate counts The design works with the processing rate of 200 Mpixels/s which is fast enough to process Full HD resolution at 30 fps in real time

Date of Award	2017 Aug 17
Original language	English
Supervisor	Pei-Yin Chen (Supervisor)