Underwater image splicing method based on multi-scale image fusion and SIFT features

An underwater image and image fusion technology, applied in image enhancement, image data processing, graphic image conversion and other directions, can solve problems such as image color cast, and achieve the effect of expanding the scope and improving the accuracy.

Active Publication Date: 2020-06-09
ZHEJIANG UNIV
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Problems solved by technology

[0004] In order to solve the above problems and fully consider the characteristics of the deep water environment, the present invention proposes an improved white balance algorithm, which can well solve the serious problem of image color cast when the light is insufficient, so that the image in deep water can also have uniform color distribution and effectively remove The color block can restore the white and gray shades of the image at the same time, and the calculation efficiency is al

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  • Underwater image splicing method based on multi-scale image fusion and SIFT features
  • Underwater image splicing method based on multi-scale image fusion and SIFT features
  • Underwater image splicing method based on multi-scale image fusion and SIFT features

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Embodiment Construction

[0106] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. Embodiments of the present invention and its implementation process are as follows:

[0107]The underwater image processed by the embodiment of the present invention is as follows figure 2 As shown, including a test image and an image to be registered. The two underwater images are taken from two angles of the same large scene, and the two images have common parts, so it is necessary to register and stitch the two underwater images to output one image. Specific steps can refer to figure 1 The flowchart in .

[0108] Step 1. Underwater image preprocessing: image enhancement

[0109] The underwater image is enhanced by using improved white balance algorithm and CLAHE algorithm based on linear interpolation.

[0110] 1.1) Use the improved white balance algorithm to perform white balance processing on underwater images.

[0111] 1.1....

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Abstract

The invention discloses an underwater image splicing method based on multi-scale image fusion and SIFT features. The method comprises the following steps: 1) performing image enhancement on an underwater image by adopting an improved white balance algorithm and a linear interpolation-based CLAHE algorithm; 2) fusing an image after image enhancement by adopting a double pyramid image fusion methodto obtain an underwater preprocessed image; 3) performing underwater image registration on the underwater preprocessed image through an improved SIFT algorithm; and 4) calculating to obtain an image affine transformation matrix, and completing final underwater image splicing by adopting a linear gradual change synthesis algorithm. Experiments prove that the method fully considers the underwater environment and underwater imaging characteristics, and can obviously improve the effects and accuracy of underwater image enhancement, registration and splicing.

Description

technical field [0001] The invention relates to an image mosaic method, in particular to an underwater image mosaic method based on multi-scale image fusion and SIFT features. Background technique [0002] With the maturity of Remote Operated Vehicle (ROV) and Autonomous Underwater Vehicle (AUV) technologies, people can easily obtain underwater optical images through ROV and AUV. However, due to the severe attenuation of light in water, the images and videos obtained by underwater optical imaging equipment have problems such as narrow field of view and low image quality. If you want to obtain images and videos with a wider field of view and more information, you will inevitably reduce their resolution and image quality. In order to solve this problem, image mosaic technology has been produced. In recent years, image stitching technology has developed rapidly, and the most widely used algorithms are SIFT and SURF. Although the SIFT algorithm has strong robustness and good ...

Claims

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Application Information

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IPC IPC(8): G06T3/00G06T3/40G06T5/50G06K9/46
CPCG06T3/0068G06T3/4038G06T5/50G06V10/44G06V10/462
Inventor 张森林王昕平刘妹琴樊臻何衍郑荣濠
Owner ZHEJIANG UNIV
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