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Image splicing method and splicing system based on grid optimization and readable storage medium

An image mosaic and grid technology, which is applied to the details of image mosaic, image enhancement, image analysis, etc., can solve the problem of inconsistent horizontal overlap rate, achieve the effect of low cost, strong versatility, and pixel alignment

Active Publication Date: 2021-05-14
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When the plane finishes framing the current column and moves a certain distance, then according to the principle of perspective, there will be a problem of inconsistent horizontal overlap ratio when framing the next column again.

Method used

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  • Image splicing method and splicing system based on grid optimization and readable storage medium
  • Image splicing method and splicing system based on grid optimization and readable storage medium
  • Image splicing method and splicing system based on grid optimization and readable storage medium

Examples

Experimental program
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Effect test

Embodiment 1

[0086] This embodiment is aimed at an island (20*15 images) between the aerial photography at a height of 10,000 meters and the horizontal line at an angle of 45 degrees to 60 degrees. The schematic diagram is as follows figure 2 As shown, the image refinement stitching process is carried out as follows:

[0087] Step A: In the single-column image stitching stage, suppress the density of local feature points to obtain the homography matrix, and derive the transfer relationship to obtain the coordinate relationship between the current images to stitch the single-column far-infrared images.

[0088] Wherein, in this embodiment, aiming at the aerial images, stitching is first performed in a single row of images, and the process is as follows:

[0089] 1) Image preprocessing: Bilateral filter noise reduction

[0090] Among them, there are many noises in the far-infrared image, which will seriously interfere with the detection and matching of feature points. Bilateral filter (Bi...

Embodiment 2

[0149] This embodiment is aimed at the continent (33*32 images) between the 10,000-meter-high aerial photography and the horizontal line at an angle of 30 degrees to 60 degrees. The schematic diagram of image acquisition is as follows figure 2 shown. The first step is to detect, match and screen out suitable feature points using SIFT and RANSAC.

[0150] The second step is to use the feature points extracted in the previous step to calculate the homography transformation matrix, and then recursively deduce the homography transformation matrix through the image position relationship to realize all the splicing of single-column images.

[0151] The third step is to perform column-to-column splicing for each column that has been spliced. First, use SIFT and RANSAC to obtain all the appropriate feature points, and then subdivide the single-column long image into 40*200 grids, and assign the grids to different The area (including overlapping area and non-overlapping area), accord...

Embodiment 3

[0156] This embodiment is aimed at 360-degree panorama stitching (9-18 images), and the images collected by the wide-angle lens are severely distorted and have high resolution. The first step is to detect, match and screen out suitable feature points using SIFT and RANSAC.

[0157] The second step is to use the feature points extracted in the previous step to calculate the homography transformation matrix, subdivide the image into 80*80 grids, and attribute the grids to different areas (including overlapping areas and non-overlapping areas), according to the Belonging to different positions, the judgment is the proportion of its regional similarity transformation and local homography transformation. The final transformation equations of different grids are slightly different, which can realize the smooth mapping of one column of images to another column of images, and at the same time help reduce Distortion, better fusion of images.

[0158] The fourth step is to use the form...

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Abstract

The invention discloses an image splicing method and splicing system based on grid optimization and a readable storage medium; the method comprises the steps: S1, obtaining a to-be-spliced image, and screening out feature points in the to-be-spliced image; s2, performing grid division on each single-row image, and calculating to obtain a transformation matrix of each grid on the image by at least combining region similarity transformation and local homography transformation; and S3, performing recursion of grid transformation based on the transformation matrix of each grid in the single-row images and by using the adjacent relation between the single-row images, thereby splicing the images in different rows. According to the method, the problem of inconsistent transverse overlapping rate is solved, and the method can be widely applied to aerial image splicing and infrared image splicing.

Description

technical field [0001] The invention belongs to the technical field of infrared image stitching, and in particular relates to an image stitching method based on grid optimization, a stitching system and a readable storage medium. Background technique [0002] Image stitching is the process of matching several images with overlapping parts. It can provide synthetic images with wide field of view, large viewing angle, high resolution and rich information. It has been widely used in panoramic shooting, medical image analysis and remote sensing Image processing and many other fields. Among them, sequential far-infrared (FIR) image sequence stitching can effectively reduce image information redundancy, synthesize wide-angle and high-resolution far-infrared images, and obtain richer and more accurate scene information. These scene information provide a very important basis for applications such as target search and tracking, detection and recognition. [0003] Usually, the extra...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40G06T7/33G06T7/38
CPCG06T3/4038G06T7/33G06T7/38G06T2207/10048G06T2200/32
Inventor 唐琎朱洪李小虎肖小月
Owner CENT SOUTH UNIV
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