To solve blurring and low contrast of images captured by outdoor visual systems under bad weather conditions

a new fast image defogging algorithm called IDA_VAM is presented; this algorithm is based on variogram and multiple structure element morphological open-and-close filter. The algorithm initially uses a variogram to obtain an accurate atmospheric optical value

and then exploits a multiple structure element morphological open-and-close filter toward the minimum channel map to obtain a rough scattering map. The transmittance map is estimated and corrected

and a bilateral filter is used for smooth operation. Recovery images are obtained by the physical model

and color adjustments are made to obtain bright

clear

and non-foggy images. Compared with other image defogging algorithms

the proposed method utilized for foggy images containing close range image

image perspective

and image with bright areas can be effective in removing the fog. The information entropy is relatively increased by 38.0%

and the contrast value is relatively increased by 34.1%. The definition value is relatively increased by 134.5%. Moreover

better restoration effect is obtained

thereby achieving a more natural

bright

and haze-free image. A large number of experimental results show that this algorithm can effectively recover color and definition of the foggy image containing a close-range image

image perspective

and image with bright areas under non-complex scenes. Clear and natural fog-free images with details of higher visibility can be obtained

and time complexity of the IDA_VAM algorithm and number of image pixels are linearly correlated

thereby meeting real-time requirements.