A Gray Image Fusion Method

Abstract

The invention provides a grayscale image fusion method. The low-rank decomposition method is used on the low dynamic image to generate the global image and the local image part. According to the low-light imaging features, two different weight maps of the decomposed image are constructed to reduce the block effect after fusion and make the visual effect of the fusion image more consistent. Human eye consistency; then use the Gaussian pyramid weight factor to fuse the decomposed low-rank image and saliency image in Laplacian space to obtain the fused low-rank image and saliency image; finally, by superimposing the low-rank image and Salient image reconstruction for high dynamic images. This method maintains the details of the darker and brighter areas of the image at the same time, and improves the dynamic range of the image.

Description

technical field [0001] The invention belongs to the technical field of high dynamic image synthesis, and in particular relates to a grayscale image fusion method based on low-rank decomposition. Background technique [0002] Common CCD sensors have a dynamic range of about 10 3 , much smaller than the dynamic range of real scenes. Additionally, images captured in low-light conditions tend to have poor visibility. Lost image details are difficult to recover due to limited dynamic range. Most of the existing multi-exposure fusion methods are aimed at color images, and the original method of constructing weight maps cannot obtain the detailed information of the over-bright and over-dark areas, resulting in low quality of the fused image. At the same time, low-illumination images have low contrast, and the fusion weight map is not constructed, resulting in uneven edge transition of the synthesized image and block effects in the image. Contents of the invention [0003] In ...

AI Technical Summary

Problems solved by technology

Also, images captured in low-light conditions tend to have poor visibility

Lost image details are hard to recover due to limited dynamic range

Most of the existing multi-exposure fusion methods are aimed at color images. The original method of constructing the weight map cannot obtain the detailed information of the over-bright and over-dark areas, resulting in low quality of the fused image.

At the same time, the contrast of low-light images is low, and the fusion weight map is not used to construct the fusion weight map, resulting in uneven edge transition of the synthesized image and block effect in the image

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