Image splicing method based on discrete wavelet transform and gradient fusion algorithm

Abstract

The invention relates to an image splicing method based on discrete wavelet transform and a gradient fusion algorithm. Firstly, projection transformation is performed on a reference image and a targetimage; feature points are extracted through an SURF algorithm, and registration is carried out through a KNN algorithm and an RANSAC algorithm; and then searching an optimal suture line to determinea fusion area and a mask image thereof, carrying out discrete wavelet transform, then respectively fusing the decomposed low-frequency area and the decomposed high-frequency area by using a gradient fusion algorithm, generating a fusion image by using inverse discrete wavelet transform, and finally splicing by using the mask image to obtain a final spliced image. According to the invention, the image splicing quality can be improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image mosaic method based on discrete wavelet transform and gradient fusion algorithm. Background technique [0002] Image stitching refers to the technology of stitching several images with overlapping areas into a seamless panorama or high-resolution image, which is widely used in computer vision, medical image analysis, remote sensing images, and virtual reality. Image fusion is an important part of image stitching, and traditional pixel-level fusion algorithms, such as average fusion algorithm and comparison fusion algorithm, will make the stitched image blurred, and the gradual-in and gradual-out fusion algorithm does not fully consider the reference image and target The difference in image clarity leads to insufficient detail information in the fused image. Discrete wavelet transform is a commonly used tool for image fusion. The traditional fusion algorithm bas...

AI Technical Summary

Problems solved by technology

Image fusion is an important part of image stitching, and traditional pixel-level fusion algorithms, such as average fusion algorithm and comparison fusion algorithm, will make the stitched image blurred, and the gradual-in and gradual-out fusion algorithm does not fully consider the reference image and target The difference in image clarity leads to insufficient detailed information in the fused image

Discrete wavelet transform is a commonly used image fusion tool. The traditional fusion algorithm based on discrete wavelet transform uses the rules based on the measurement of regional characteristics. When this algorithm is applied to color images, the fusion image will become blurred.

Images