Image dehazing method and system based on dark channel and non-local prior

Abstract

The invention discloses an image dehazing method and system based on a dark channel and a non-local prior, which belongs to the technical field of image information processing. The image dehazing method can reasonably recover a degraded image collected in the haze weather. The method comprises the following steps of (1) calculating a dark channel image of a hazed image; (2) estimating the atmospheric light intensity of the hazed image according to the dark channel image; (3) estimating the transmissivity of the image based on the non-local prior; (4) correcting a transmittance image; and (5) using an atmospheric scattering model to restore a dehazed image. The invention also discloses an image dehazing system based on the dark channel and the non-local prior. The invention can restore scene information in the image realistically and naturally, and the algorithm has the advantages of low complexity, fast running speed and wide application prospect.

Description

technical field [0001] The invention belongs to the technical field of image information processing, in particular to an image defogging method and system based on dark channel and non-local prior. Background technique [0002] At present, outdoor vision systems such as cameras for security monitoring are more and more widely used. Moreover, in recent years, intelligent vision systems such as intelligent visual monitoring systems, intelligent vehicle visual navigation systems, and intelligent robot vision systems have developed rapidly. The quality of the image collected by the vision system directly affects the stability of the system. In severe weather conditions such as fog and haze, due to the influence of the scattering of tiny particles in the atmosphere, the acquired image will have problems such as reduced contrast, decreased saturation, and hue shift, which interferes with the extraction of image features and directly affects the effectiveness of the visual system....

AI Technical Summary

Problems solved by technology

Berman D et al. proposed a non-local prior-based defogging method. Most of the current defogging algorithms are based on block prior methods. Blocky effect of image after fog

The method based on non-local prior is based on the operation of pixels, so it will not produce block effect, and the algorithm runs fast and can meet the real-time requirements. However, the algorithm based on non-local prior has incomplete defogging and sky area Distortion and other issues

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