Research Of Image Dehazing Algorithm For Night Image Base Fusion

Images of outdoor scene those taken in hazy weather condition are degraded due to absorption and scattering of atmospheric aerosol particles.The degradation includes reduction of contrast and distortion of color,etc.At present,the research of image restoration algorithm for hazy image with uniform illumination(daytime)has already achieved significant results.However,the research of image restoration algorithm for hazy image with non-uniform illumination(nighttime)has little results.Nighttime haze removal is more difficult,since nighttime hazy images contain degradation more serious than daytime's due to illumination,resulting in lower brightness,lower contrast,uneven illumination,chromatic aberration,and higher noise,etc.Therefore,in this paper we study the image restoration algorithm for nighttime hazy image.This paper includes the follow two contents:(1)In this thesis,a fusion based haze image restoration framework is proposed based on the characteristics of haze images(uneven illumination,low brightness,and blurred details).A new luminance adjustment curve is proposed for uneven illumination and low overall brightness.In order to ensure the enhancement of brightness and avoid exposure,the light map is generated.In detail,the light color of the object is relatively bright in the shallow depth of field,that is,the saturation is higher,but the brightness is low.With the increase of the depth of field,the haze increases,but the saturation decreases.Based on this,we derive a new transmission graph estimation method and generate detail maps.In the process of merging the above two images,three weights are used(weight of the brightness,the weight of saturation,the weight of the saliency)to ensure that the better part of each image can be retained and the effect of haze removal can be achieved.)(2)To improve our algorithm,we use different enhancement methods to get illumination map for different characteristics of night illumination area and insufficient area.Image segmentation based on human eyes is proposed,which effectively partitioned the image into regions of different attributes.According to the size of the area,the coefficient of illumination adjustment is automatically generated to increase the applicability of the algorithm.To generate detailed images,we use the new nocturnal haze degradation model to explain the influence of the bright area phenomenon.The splendor is separated by the use of the smoothing hypothesis.Then we use guided filtering to enhance the exposure.Thus the effect of dehaze is improved.