Design and Implementation of an Efficient Haze Removal Algorithm

Abstract

In the real-time outdoor applications of computer vision-based surveillance systems haze removal that can recover clear images from foggy ones is an essential preprocessing technique for object detection In this dissertation an efficient haze removal method suitable for hardware design is proposed to obtain high quality fog-free static images and videos Based on the atmosphere scattering model and the dark channel prior method the atmospheric light of the whole image and the transmission map could be extracted Instead of using a single global atmospheric light to restore foggy image a local atmospheric light estimation method is applied in the proposed design to achieve optimal results To ensure that the overall image is consistent without block artifacts dynamic adjustment of local atmospheric light is calculated based on global atmospheric light Furthermore 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 before To achieve the requirement of real-time applications for both static and dynamic images an implementation of very-large-scale integration (VLSI) architecture for the proposed algorithm is presented By using TSMC 0 13-um technology the design yielded a processing rate of approximately 200 Mpixels/s which is rapid enough to facilitate Full HD resolution at 30 fps in real-time

Date of Award	2020
Original language	English
Supervisor	Pei-Yin Chen (Supervisor)