An Efficient Adaptive Denoising and Dehazing Technique
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Abstract
Image haze removal has become an important research direction in the field of computer vision because of the vast development and increasing demand of its applications. Outdoor images that are captured in bad weather are degraded due to factors like noise and haze. These factors seriously affect the visibility of the image. Images may contain impulse noise which is produced by the sensor and circuitry of image-capturing devices like cameras. Images may also contain haze, which is formed due to the combination of two fundamental phenomena namely, attenuation and the airlight. Attenuation reduces the image contrast and air light increases the whiteness in the image, thereby making the images unclear. This work presents a hybrid approach for denoising and dehazing a single noisy and hazy image. First, the input image is passed through an adaptive median filter to remove the impulse noise. Then the resultant image is dehazed using simple color attenuation prior. The experimental results show that the visual quality of the output images are much better than the original input images, which proves the efficiency of this method. Keywords: Adaptive Median Filter ; Atmospheric Scattering Model ; Color attenuation prior ; Denoising ; Haze removal ; Impulse noise ;
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