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An image fusion and mosaic method based on parallel computing algorithm

A fusion stitching and parallel computing technology, applied in the field of image processing, can solve problems such as area size limitations, and achieve the effect of wide viewing angle, rich information, and simple and clear program structure

Active Publication Date: 2019-03-12
RES INST OF FOREST RESOURCE INFORMATION TECHN CHINESE ACADEMY OF FORESTRY +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] However, limited by the size of the area that can be covered by a remote sensing image, especially when using high-resolution remote sensing images, it is necessary to investigate various resources in a certain administrative area, geographical division, watershed, etc. In the current situation and changing situation, only one scene of remote sensing images is far from meeting the requirements of practical applications, and the image sequence of multiple scenes with a certain overlap rate in spatial position is synthesized into one scene through fusion and splicing technology with seamless, New images with wide field of view and information of each image sequence have become a basic requirement for remote sensing images in practice

Method used

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  • An image fusion and mosaic method based on parallel computing algorithm
  • An image fusion and mosaic method based on parallel computing algorithm
  • An image fusion and mosaic method based on parallel computing algorithm

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Experimental program
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Embodiment 1

[0042] Embodiment 1: as figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 , Image 6 and Figure 7 Shown, a kind of image fusion mosaic method based on parallel computing algorithm contains following steps;

[0043] Step 1. Set the stitching method;

[0044] Step 2. Obtain the basic information of the two scenes to be fused and stitched;

[0045] Step 3, creating a spatial correspondence between the two scene images through data resampling;

[0046] Step 4, performing the fusion stitching of the two scene images;

[0047] Step 5, saving the image file after fusion and splicing;

[0048] Step 6. End fusion splicing.

[0049] Also contains the following steps;

[0050] In step 1, the single-band two-scene images that have been corrected and registered are fused and stitched, and in order to improve the efficiency of the program and reduce invalid control and judgment work, it is agreed that the pixels in the background position in the registered image , which i...

Embodiment 2

[0062] Embodiment 2: as figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 , Image 6 and Figure 7 As shown, an image fusion stitching method based on a parallel computing algorithm, due to the limitation of the coverage of a scene remote sensing image, especially when using a remote sensing image with a high ground resolution To investigate the status and changes of various resources, the limitations of single-scene images are very obvious.

[0063] Fusion and splicing of multi-scene images into one scene image has become a basic operation process necessary for remote sensing images in practical applications. The traditional fusion stitching algorithm is based on the traditional serial computing algorithm, but for remote sensing image data, with the improvement of spatial resolution, the data volume of single scene image is getting larger and larger. When fusion splicing, limited by computer resources and traditional serial computing algorithms, it is more and mo...

Embodiment 3

[0064] Embodiment 3: as figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 , Image 6 and Figure 7 Shown, a kind of image fusion mosaic method based on parallel computing algorithm contains following steps;

[0065] like figure 2 As shown, the overall flow chart of the two-view image fusion and stitching method based on the parallel computing algorithm,

[0066] Image stitching starts;

[0067] Step 1. Set the fusion splicing method;

[0068] Step 2. Obtain the basic information of the image;

[0069] Step 3, resampling to create a spatial correspondence between the two scene images;

[0070] Step 4, performing the fusion stitching of the two scene images;

[0071] Step 5, saving the image file after fusion and splicing;

[0072] Step 6. End fusion splicing.

[0073] The steps for setting the image fusion stitching method in step 1 are as follows:

[0074] For the convenience of description, only three fusion splicing methods (RHPJ_FS) are given (including...

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Abstract

The invention relates to an image fusion mosaic method based on a parallel computing algorithm, belonging to the technical field of image processing. Comprising the steps of: Setting splicing mode; Acquiring basic information of two images to be fused; Creating spatial correspondence between two scene images by data resampling; Fusion and mosaic of two images; Save the image file after fusion splicing; End fusion splicing. The invention puts forward the technical idea of exchanging space for time. By establishing the space between two scene images and the one-to-one correspondence relation onthe image data, the invention achieves the data processing ability suitable for parallel calculation, simplifies the algorithm logic relation, strengthens the program structure, automates the operation, and has high efficiency and high speed.

Description

technical field [0001] The invention relates to an image fusion stitching method based on a parallel computing algorithm, which belongs to the technical field of image processing. Background technique [0002] Image stitching usually includes three basic steps of image preprocessing, image registration and image fusion. Image preprocessing mainly refers to the geometric distortion correction and noise suppression of the image, so that the reference image and the image to be stitched have no obvious geometric distortion. [0003] The image registration criterion is the most critical step in image mosaicing, and the quality of image registration methods is directly related to the efficiency and accuracy of image registration. At present, the most commonly used registration methods can be roughly divided into two categories: area registration method and feature registration method. [0004] Based on the area correlation registration method, its characteristic is to select a r...

Claims

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Application Information

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IPC IPC(8): G06T3/40G06T5/50
CPCG06T3/4038G06T5/50G06T2207/20221
Inventor 凌成星孟献策鞠洪波刘华赵峰张怀清陈永富王晓慧肖鹏
Owner RES INST OF FOREST RESOURCE INFORMATION TECHN CHINESE ACADEMY OF FORESTRY
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