Visibility Restoration for Single Hazy Image Using Dual Prior Knowledge

Dengyin Zhang,Haoxing Qin,Zhenfei Gu,Mingye Ju

doi:10.1155/2017/8190182

Abstract

Single image haze removal has been a challenging task due to its super ill-posed nature. In this paper, we propose a novel single image algorithm that improves the detail and color of such degraded images. More concretely, we redefine a more reliable atmospheric scattering model (ASM) based on our previous work and the atmospheric point spread function (APSF). Further, by taking the haze density spatial feature into consideration, we design a scene-wise APSF kernel prediction mechanism to eliminate the multiple-scattering effect. With the redefined ASM and designed APSF, combined with the existing prior knowledge, the complex dehazing problem can be subtly converted into one-dimensional searching problem, which allows us to directly obtain the scene transmission and thereby recover visually realistic results via the proposed ASM. Experimental results verify that our algorithm outperforms several state-of-the-art dehazing techniques in terms of robustness, effectiveness, and efficiency.

Highlights

Experimental results verify that our algorithm outperforms several state-of-the-art dehazing techniques in terms of robustness, effectiveness, and efficiency
Outdoor images captured in bad weather are prone to yield poor visibility, such as fade surface color, reduced contrast, and blurred scene details (see Figure 1(a))
Similar to [28], we introduce the generalized Gaussian distribution model (GGDM) [31] to approximate the atmospheric point spread function (APSF), and the modified APSF for neighborhood can be modeled as hAPSF (x, y; T, q)

Summary

Introduction

Outdoor images captured in bad weather are prone to yield poor visibility, such as fade surface color, reduced contrast, and blurred scene details (see Figure 1(a)). Ancuti [16] first present a fusion-based dehazing strategy; the main advantage of this method is its linear complexity and it can be implemented in real time, yet the dehazing effect is highly dependent on the haze-feature weight maps. He et al [17] discovered the dark channel prior (DCP) which is a kind of statistics of the haze-free outdoor images.

The Redefined Atmospheric Scattering Model

The Proposed Algorithm

Experiments

Findings

Discussion and Conclusions