Multi-scale Retinex image defogging method based on MATLAB

Abstract

The invention provides a multi-scale Retinex image defogging method based on MATLAB. The multi-scale Retinex image defogging method comprises the following steps: 1, acquiring R, G and B components; 2, sequentially carrying out low-pass filtering processing and high-pass filtering processing on one component in the step 1; 3, performing low-pass filtering processing on the original image; 4, in the logarithmic domain, subtracting the image subjected to low-pass filtering in the step 3 from the original image to obtain a high-frequency image; wherein the high-frequency image comprises three high-frequency enhanced images; 5, performing inverse logarithm taking on the high-frequency image to obtain a channel enhanced image of the component in the step 2; 6, executing the step 2 until the enhanced image of the R channel, obtaining the enhanced image of the G channel and the enhanced image of the B channel; and 7, synthesizing an enhanced image of the R channel, an enhanced image of the Gchannel and an enhanced image of the B channel by applying a cat function. Two characteristics of tone reproduction and dynamic range compression can be considered, the color of the image is restoredto a large extent, and the defogging effect is remarkable.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a MATLAB-based multi-scale Retinex image defogging method. Background technique [0002] In the foggy environment, due to the influence of atmospheric scattering, the visibility and contrast of the captured scenes are reduced, which directly affects the safety of aviation, shipping and road traffic. At the same time, various outdoor monitoring systems, such as video surveillance systems, are often does not work reliably. Therefore, simple and effective image dehazing is of great significance to improve the reliability and robustness of vision systems. [0003] In the prior art, the processing of foggy images mainly focuses on the algorithm level of software development on the PC platform. Although these algorithms can achieve the purpose of defogging, because they are all software processing, they take a long time and cannot meet the high-speed and high-quality require...

AI Technical Summary

Problems solved by technology

Although these algorithms can achieve the purpose of defogging, because they are all software processing, they take a long time and cannot meet the high-speed and high-quality requirements of real-time monitoring chips such as ISP ((Image Signal Processing, Image Signal Processing)

Although some scholars have tried to realize the dehazing algorithm in FPGA (Field-Programmable Gate Array, Field Programmable Gate Array) and other hardware, they have degraded their own dehazing algorithm. Fog effects are bound to be affected

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