International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 04 Issue: 07 | July -2017
p-ISSN: 2395-0072
www.irjet.net
Visibility Enhancement of Hazy Images using Depth Estimation Concept M. Gopika1, M. Sirisha2 1PG
Student, Dept. of ECE, Chalapathi Institute of Engineering and Technology, Lam, Andhra Pradesh, India1 Professor, Dept. of ECE, Chalapathi Institute of Engineering and Technology, Lam, Andhra Pradesh,India2 ---------------------------------------------------------------------***--------------------------------------------------------------------2Assistant
Abstract - Image Enhancement is used to improve the
contrast of the image having luminance. Image enhancement process removes the distortion from the image and improves the quality of the image. The image is captured in the outdoor scene are highly despoiled due to the reduced lighting situation or due to the soil particles. So, due to these particles the irradiation coming from the object is scattered and absorbed and hence the phenomenon of haze and fog occurs. Most of the researchers of the previous decade have proposed various methodologies to improve the visibility of the hazy images under the atmospheric conditions. This work proposes a methodology using depth estimation concept to improve the visibility of hazed images due to atmospheric troubles. The proposed methodology concentrated only on the depth estimation of the surface of the scene to camera lens and gamma correction factor has been applied at the final stage in order to obtain the output image as perfect as visible for the human eyes.
Fig -1: Haze formation concept
Moreover, most automatic systems, which strongly depend on the definition of the input images, failed to work normally caused by the degraded images. Therefore, improving the technique of image haze removal will benefit many image understanding and computer vision applications such as aerial, imagery, image classification, image/video retrieval, remote sensing and video analysis and recognition [1-5].
Key Words: Image enhancement, Haze, Depth estimation, Gamma correction, weight maps, visibility restoration.
1. INTRODUCTION The main purpose of image processing is to identify, understand, interpret and investigate the data from the image pattern. Outdoor images taken in bad weather (e.g., foggy or hazy) usually lose contrast and fidelity, resulting from the fact that light is absorbed and scattered by the turbid medium such as particles and water droplets in the atmosphere during the process of propagation. Haze and fog are an atmospheric effect, but they are different: haze is thin and translucent effect while fog is thick and opaque. The haze is formed in the atmosphere due to the airlight and attenuation process. The concept of haze formation has illustrated in Figure1.
Haze removal (Dehazing) is highly desired in consumer/computational photography and computer vision applications. The process of removing haze can significantly increase the visibility of scene and correct the color shift caused by the airlight. In general, the haze-free image is more visually pleasing. Majority of the computer vision algorithms, from low-level image analysis to high-level object recognition, usually assume that the input image (after radio metric calibration) is scene radiance. The performance of many vision algorithms (e.g. feature detection, filtering, and photometric analysis) will inevitably suffer from the biased and low-contrast scene radiance. Finally haze removal can provide depth information and benefit many vision algorithms and advanced image editing. Haze or fog can be a useful depth clue for scene understanding. Visibility restoration refers to different methods that aim to enhance the visibility of an image. The
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