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首页> 外文期刊>Journal of Theoretical and Applied Information Technology >THE SYNTHETIC HAZE SIMULATION BASED ON VISIBILITY RANGE FOR DEHAZING METHOD IN SINGLE IMAGE
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THE SYNTHETIC HAZE SIMULATION BASED ON VISIBILITY RANGE FOR DEHAZING METHOD IN SINGLE IMAGE

机译:基于单幅图像中去除湿方法的可见度范围的合成雾霾模拟

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Outdoor images are typically degraded by light scattering and absorption from aerosols, such as dust, mist, and smoke in the atmosphere. Because of poor visibility, dimmed brightness, low contrast, and colour distortion, these phenomenons affect the captured image. Therefore, it is a critical challenge to recover pictures taken in a haze condition, which is called image dehazing. The primary aim of image dehazing is to improve details on visibility, edge, and texture and retain the image structure and colours without data loss. There are no proven benchmarks for their assessment, despite the many algorithms suggested for single image dehazing. In previous publications, arbitrary comparisons were mostly focused on a small number of images, with different publications using different sets of images. This paper presents a new dataset that includes image pairs of hazy and corresponding outdoor images that are haze-free (ground-truth). Most of the current hazy database presented in a single image simulated synthetic haze indicated complicated calculation of the depth map. Unlike most of the current dehazing databases, a synthetic haze, which is determined by the atmospheric scattering algorithm derived from the actual distance from the camera to the scene object, has simulated hazy images. In the separate range, the synthetic haze derivation referred from the meteorological range explicitly based on haze conditions. On a clear day as referred to as a low Air Pollutant Index, this experiment simulated synthetic haze in the Malaysian outdoor scene. The haze simulation illustrates how this approach can lead to better outcomes in the measurement of image quality than the current state-of-the-art dehazing method.
机译:室外图像通常通过光散射和从气溶胶的吸收而降解,例如灰尘,雾气和大气中的烟雾。由于可见性差,暗淡亮度,低对比度和彩色失真,这些现象影响了捕获的图像。因此,恢复在雾度条件下拍摄的照片是一个关键挑战,这被称为图像脱落。图像脱水的主要目的是改善可见性,边缘和纹理的细节,并在没有数据丢失的情况下保留图像结构和颜色。尽管为单幅图像脱皮所建议的许多算法,但没有经过验证的基准。在以前的出版物中,任意比较主要集中在少数图像上,使用不同的图像具有不同的出版物。本文介绍了一个新的数据集,包括图像对的朦胧和相应的户外图像,这些户外图像是无雾的(地面真理)。在单个图像中呈现的大多数当前朦胧数据库模拟合成雾霾表明了对深度图的复杂计算。与大多数当前的脱水数据库不同,由源于从相机到场景对象的实际距离的大气散射算法确定的合成雾霾具有模拟朦胧图像。在单独的范围内,基于雾度条件明确地从气象范围内提到的合成雾度衍生。在作为低空气污染物指数的晴朗日,这项实验模拟了马来西亚户外场景的合成阴霾。雾度模拟说明了这种方法如何在图像质量的测量中导致更好的结果,而不是当前的最先进的去吸附方法。

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