Design and Development of Visibility Restoration Techniques for Weather Degraded Images

Abstract

The visibility of outdoor images is greatly degraded due to the presence of fog, haze, smog, etc. The poor visibility may cause the failure of computer vision applications such as intelligent transportation systems, surveillance systems, and object tracking. To resolve this problem, many image restoration techniques have been developed. These techniques play an important role in improving the performance of various computer vision applications. Due to this, the researchers are attracted toward the visibility restoration techniques. It has been found that the majority of existing techniques suffer from various issues such as edge distortion, color distortion, texture distortion, halo artefacts, gradient reversal artefacts, and poor computational speed. To overcome these issues, various visibility restoration techniques are proposed in this research work. A Dark channel prior (DCP) based visibility restoration technique is implemented by designing a Gain intervention based trilateral filter (GITF) for fog affected images. GITF is able to remove the fog from weather degraded images in an effective manner. It is tested on ten (five benchmarks and five real-life) roadside foggy images. The experimental results reveal that GITF has lesser number of artefacts and preserve more significant edges as compared to the existing restoration techniques. GITF is computationally faster than the existing techniques. Therefore, GITF is more suitable for real-time intelligent transportation systems. Although, GITF outperforms the existing techniques in case of foggy images, it is not so effective against remote sensing hazy images. Therefore, a fourth-order partial differential equation based trilateral filter (FPDETF) based restoration technique is proposed to restore hazy remote sensing images. FPDETF is able to reduce halo and gradient reversal artefacts. It also preserves the radiometric information of restored images. The visibility restoration phase is also refined to reduce the color distortion of restored images.