针对有雾天气下无人机航拍视觉系统的能见度低,航拍图像对比度和色彩保真度差等问题,基于暗原色先验规律以及雾图的物理模型提出了一种雾天降质图像去雾处理技术。从图像复原和增强两个角度出发,分别建立了户外图像全局去雾和对比度自...针对有雾天气下无人机航拍视觉系统的能见度低,航拍图像对比度和色彩保真度差等问题,基于暗原色先验规律以及雾图的物理模型提出了一种雾天降质图像去雾处理技术。从图像复原和增强两个角度出发,分别建立了户外图像全局去雾和对比度自适应调整的最优化模型,从而能够直接复原得到高质量的去除雾干扰的图像并且估算出雾的浓度。对一系列户外带雾图像的分组实验表明,该方法可以快速有效地提高带雾图像的对比度和色彩清晰度,获得满意的视觉效果。另外,该方法克服了Kai ming He方法处理时间过长的缺陷,平均处理时间仅为原方法的10%左右,显著缩短了运算时间,为在工程项目中实现图像的实时去雾处理提供了理论依据。展开更多
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 tech...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.展开更多
文摘针对有雾天气下无人机航拍视觉系统的能见度低,航拍图像对比度和色彩保真度差等问题,基于暗原色先验规律以及雾图的物理模型提出了一种雾天降质图像去雾处理技术。从图像复原和增强两个角度出发,分别建立了户外图像全局去雾和对比度自适应调整的最优化模型,从而能够直接复原得到高质量的去除雾干扰的图像并且估算出雾的浓度。对一系列户外带雾图像的分组实验表明,该方法可以快速有效地提高带雾图像的对比度和色彩清晰度,获得满意的视觉效果。另外,该方法克服了Kai ming He方法处理时间过长的缺陷,平均处理时间仅为原方法的10%左右,显著缩短了运算时间,为在工程项目中实现图像的实时去雾处理提供了理论依据。
文摘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.
