A Novel Retinex Algorithm Based on Dark Channel Prior Model
Wei Zha · Dianzi xuebao · 2013
Current Retinex algorithm applied in foggy image enhancement with fixed filter can't adapt to the situation of various depth of field and atomization.This paper presents a self-adaptive filter Retinex algorithm based on dark channel prior model. The model of dark channel prior reflects the information of field depth and distribution of atmosphere in foggy image.We are inspired to design an self-adaptive filter according to the local value of dark channel using different filters in different depth of field and foggy area to estimate the illumination component of the image,and to achieve the clarity of foggy image.Finally,we compare the result of the proposed algorithm with the result of HE algorithm and result of fixed filter MSR algorithm using the subjective observation and objective data analysis method.The comparison shows that the result of Retinex algorithm based on dark channel prior has better detail of image and global effect than that of the HE algorithm and fixed filter MSR algorithm.