Retinex image enhancement method based on Laplacian pyramid

Abstract

The invention provides a Retinex image enhancement method based on a Laplacian pyramid. The method comprises the following three processes: firstly, carrying out multi-scale convolution on an originalimage, carrying out convolution by adopting three 3 * 3 Gaussian convolution kernels, and obtaining R, G and B channel feature maps with different scales; secondly, estimating an incident component by adopting a Retinex algorithm and enhancing colors; enhancing details of reflective components; and finally, carrying out linear weighted fusion on the color enhanced image and the detail enhanced image to obtain an enhanced image. According to the method, more details of the image are acquired by adopting multi-scale convolution, image enhancement is carried out by utilizing an MSRCR algorithm,and Gamma correction is carried out on an incident component to realize color enhancement. Bilateral filtering denoising is carried out on the reflection component to reduce noise interference, and image detail information is extracted through a Laplacian pyramid; and linear weighted fusion is carried out on the color enhanced image and the detail enhanced image to realize image enhancement.

Description

technical field [0001] The invention relates to a Retinex image enhancement method based on Laplacian pyramid. Background technique [0002] The rapid development of computer technology has promoted the wider application of computer vision, and the improvement of image quality has become a common concern in the field of digital image processing. Images captured in low light, foggy and hazy weather have low resolution. There are two commonly used processing methods for low-quality images, which are based on image enhancement methods and image restoration methods based on physical models. Through the above operations, you can Improve image quality. [0003] Foggy image enhancement method is to enhance the region of interest in the image without considering the cause of image quality degradation. The method is to enhance the high-frequency components in the image and enhance the edge contour information to make the details more obvious. The image restoration method considers ...

AI Technical Summary

Problems solved by technology

Due to the color distortion problem of the SSR algorithm and the MSR algorithm, the MSRCR algorithm is proposed. This algorithm introduces a nonlinear function of the original image chromaticity in the restoration process to compensate for the color loss information of the MSR algorithm, which can preserve image color and enhance contrast. , but there are partial differences between the enhanced image color and the original color, resulting in overexposure

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