Simulation of Hazy Image and Validation of Haze Removal Technique  

作　　者：Aditi Sarker Morium Akter Mohammad Shorif Uddin 

机构地区：[1]Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh

出　　处：《Journal of Computer and Communications》2019年第2期62-72,共11页电脑和通信（英文）

摘　　要：Haze hampers the performance of vision systems. So, removal of haze appearance in a scene should be the first-priority for clear vision. It finds wide spectrum of practical applications. A good number of dehazing techniques have already been developed. However, validation with the help of ground truth i.e. simulated haze on a clear image is an ultimate necessity. To address this issue, in this work synthetic haze images with various haze concentrations are simulated and then used to confirm the validation task of dark-channel dehazing mechanism, as it is a very promising single image dehazing technique. The simulated hazy image is developed using atmospheric model with and without Perlin noise. The effectiveness of dark-channel dehazing method is confirmed using the simulated haze images through average gradient metric, as haze reduces the gradient score.Haze hampers the performance of vision systems. So, removal of haze appearance in a scene should be the first-priority for clear vision. It finds wide spectrum of practical applications. A good number of dehazing techniques have already been developed. However, validation with the help of ground truth i.e. simulated haze on a clear image is an ultimate necessity. To address this issue, in this work synthetic haze images with various haze concentrations are simulated and then used to confirm the validation task of dark-channel dehazing mechanism, as it is a very promising single image dehazing technique. The simulated hazy image is developed using atmospheric model with and without Perlin noise. The effectiveness of dark-channel dehazing method is confirmed using the simulated haze images through average gradient metric, as haze reduces the gradient score.

关 键 词：HAZE SIMULATION VALIDATION Perline Noise DEPTH Map Dark-Channel Prior 

分 类 号：R73[医药卫生—肿瘤]