In order to solve the deficiencies of existing image defogging algorithms, such as inaccurate estimation of the transmission in the sky or bright areas, image color distortion and serious loss of details, an adaptive transmission defogging algorithm based on linear transformation is proposed. Firstly, input image is converted to Ycbcr space to extract the brightness componentan, and anti-S type function is constructed to reduce the influence of the highlighted pixels. Then a linear transformation model is used to enhance the compressed luminance component, and a Gaussian function is adopted to convolve the luminance component to obtain an adaptive control parameter; Combining linear transformation model and the adaptive control parameter can approximate the minimum color channel of the fog-free image, and further obtain an accurate estimate of the transmission. Finally, the restored image is acquired by using the atmospheric scattering model and local atmospheric light in reverse. In the experimental verification part, visible edges, average gradients, saturated pixels, and structural similarity are used as objective evaluation indicators. Objective data illustrates that all indicators of the proposed method achieves better performance. In terms of subjective effects, the proposed algorithm is superior to several existing defogging algorithms, which can accurately estimate the transmission, effectively remove image fog interference and improve the color distortion of the sky or bright areas, improve image visibility, and restore more details and edge information of the image.
