A Review of Image Restoration based Image Defogging Algorithms

Bansal, Bindu; Sidhu, Jagroop Singh; Jyoti, Kiran

doi:10.5815/ijigsp.2017.11.07

Cited by 14 publications

(2 citation statements)

References 42 publications

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“…Bansal et al [17] discussed a number of a single image and multiple image dehazing algorithms for image restoration. e paper is a comparison between different state-of-the-art techniques and elaborates the advantages and disadvantages summarizing future scope as well.…”

Section: Related Workmentioning

confidence: 99%

Single Image Dehazing and Edge Preservation Based on the Dark Channel Probability-Weighted Moments

Yousaf

Habib

Mehmood

et al. 2019

Mathematical Problems in Engineering

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e method of single image-based dehazing is addressed in the last two decades due to its extreme variating properties in different environments. Different factors make the image dehazing process cumbersome like unbalanced airlight, contrast, and darkness in hazy images. Many estimating and learning-based techniques are used to dehaze the images to overcome the aforementioned problems that suffer from halo artifacts and weak edges. e proposed technique can preserve better edges and illumination and retain the original color of the image. Dark channel prior (DCP) and probability-weighted moments (PWMs) are applied on each channel of an image to suppress the hazy regions and enhance the true edges. PWM is very effective as it suppresses low variations present in images that are affected by the haze. We have proposed a method in this article that performs well as compared to stateof-the-art image dehazing techniques in various conditions which include illumination changes, contrast variation, and preserving edges without producing halo effects within the image. e qualitative and quantitative analysis carried on standard image databases proves its robustness in terms of the standard performance evaluation metrics.

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Section: Related Workmentioning

confidence: 99%

Single Image Dehazing and Edge Preservation Based on the Dark Channel Probability-Weighted Moments

Yousaf

Habib

Mehmood

et al. 2019

Mathematical Problems in Engineering

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“…The main activities like object recognition, tracking, and monitoring in outdoor camera system often disruption with the weather, as haze and fog [3]. Haze is tiny particles, and vapors distribute in the air that may reduce the performance of the vision system as light disturbance, and uniform scene distorted [4]. However, this problem occurred by scene depth and irregular light received across the line of the observance [5]- [7].…”

Section: Introductionmentioning

confidence: 99%

Uniform Distorted Scene Reduction on Distribution of Colour Cast Correction

Talib

Nasruddin

Abdullah

2019

Int. J. Adv. Sci. Eng. Inf. Technol.

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Scene in the photo occulated by uniform particles distribution can degrade the image quality accidently. State of the art pre-processing methods are able to enhance visibility by employing local and global filters on the image scene. Regardless of air light and transmission map right estimation, those methods unfortunately produce artifacts and halo effects because of uncorrelated problem between the global and local filter's windows. Besides, previous approaches might abruptly eliminate the primary scene structure of an image like texture and colour. Therefore, this study aims not solely to improve scene image quality via a recovery method but also to overcome image content issues such as the artefacts and halo effects, and finally to reduce the light disturbance in the scene image. We introduce our proposed visibility enhancement method by using joint ambience distribution that improves the colour cast in the image. Furthermore, the method is able to balance the atmospheric light in correspondence to the depth map accordingly. Consequently, our method maintains the image texture structural information by calculating the lighting estimation and maintaining a range of colours simultaneously. The method is tested on images from the Benchmarking Single Image Dehazing research by assessing their clear edge ratio, gradient, range of saturated pixels, and structural similarity metric index. The scene image restoration assessment results show that our proposed method had outperformed resuls from the Tan, Tarel and He methods by gaining the highest score in the structural similarity index and colourfulness measurement. Furthermore, our proposed method also had achieved acceptable gradient ratio and percentage of the number of saturated pixels. The proposed approach enhances the visibility in the images without affecting them structurally.

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