Restoration of misty images based on wavelet transform and atmospheric scattering model

In conditions of low visibility, the scattering effect of atmospheric particles can result in images captured by cameras exhibiting a number of problems, including reduced contrast, color distortion, and blurred details. These issues can have a significant impact on the clarity and recognition of the images. In response to these issues, this study combines atmospheric scattering models with wavelet transform, introduces non-blind deconvolution algorithms and, finally, designs a special gamma correction function to ultimately develop a new foggy image restoration model. The relevant outcomes showed that when the dehazing model processed most image samples, its edge preservation was mainly concentrated in a relatively high range, namely [0.80, 0.96]. From the perspective of the structural similarity index, the discrete wavelet transform achieved the highest value of 0.8264. In addition, the peak signal-to-noise ratio of the improved gamma correction function was 18.346. The proposed algorithm for restoring foggy images has the advantages of high clarity, strong color restoration ability, and fast restoration speed, providing more reliable and efficient image data support for applications in related fields.