Image defogging method based on mathematic morphology and multi-resolution fusion

Abstract

The invention relates to an image defogging method based on a mathematic morphology and multi-resolution fusion. The method includes the following steps: firstly, calculating a minimum value of three channels in a misty image and using the minimum value as a high-resolution component and carrying out morphological opening operation on the high-resolution component so as to obtain a low-resolution component; using a guiding filter to carry out image fusion on the high-resolution and low-resolution components so as to obtain an atmospheric light curtain map; and at last, calculating an atmospheric light intensity value and adopting an atmospheric scattering model to carry out restoring processing on the misty image. The image defogging method based on the mathematic morphology and multi-resolution fusion has the following advantages: (1) multi-resolution fusion is adopted to estimate an atmospheric light curtain so that effect is obvious and execution speed is high; (2) the atmospheric light intensity value is calculated through a grey level histogram so that the calculation is simple and effective; (3) the method is applicable to color images or gray level images and applicable to optical images or other images so that the method has universality.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to an image defogging method based on mathematical morphology and multi-resolution fusion, which can be used for fast defogging of a single image or continuous video. Background technique [0002] Fog is a common natural phenomenon. In the images taken in foggy days, due to the scattering effect of suspended particles in the atmosphere, the brightness of the captured images increases, the contrast decreases, and the recognizability of the images decreases. Even for photos taken under sunny conditions, the sharpness of the photos will be affected due to atmospheric scattering. In every real scene, photo clarity suffers because of the fact that light bounces off surfaces and scatters into the air before reaching the camera. This is because certain factors in the air (such as aerosols, dust, fog and smoke, etc.) can cause the surface color of the object to fade and cause the contrast of ...

AI Technical Summary

Problems solved by technology

Enhancement methods based on image processing include global image enhancement methods, such as global histogram equalization, homomorphic filtering, wavelet method, Retinex algorithm, etc., or localized image enhancement methods, such as local histogram equalization, local contrast Enhancement method; the above image processing algorithm is relatively simple, and the effect of defogging for complex scenes is general

Restoration methods based on physical models include restoration based on partial differential equations, restoration based on depth relations, and restoration based on prior information; the above image processing algorithms are relatively complex, and can better deal with the effects of fog in complex scenes, but High computational complexity, difficult implementation, and slow processing speed make it difficult to realize real-time processing of defogging processing, so that it cannot be efficiently applied to video defogging processing

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