Kinect deep image remediation method based on colorful image segmentation

A technology of color image and restoration method, which is applied in the field of image processing and can solve problems such as intractable large holes and difficult depth values.

Active Publication Date: 2015-06-03
山东智瞰深鉴信息科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing Kinect depth map repair method is difficult to deal with large holes, and it is also difficult to give a more accurate depth value at the hole formed due to boundary occlusion.

Method used

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  • Kinect deep image remediation method based on colorful image segmentation
  • Kinect deep image remediation method based on colorful image segmentation
  • Kinect deep image remediation method based on colorful image segmentation

Examples

Experimental program
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Effect test

Embodiment 1

[0055] Such as Figure 1-9 shown.

[0056] A Kinect depth map restoration method based on color image segmentation, the steps are as follows:

[0057] A. Acquire color images and depth maps;

[0058] Using a Kinect camera to simultaneously acquire a color image and a depth map, aligning the color image and the depth map; figure 2 for color images, Figure 4 is the depth map, and the scene is a standing person in the laboratory;

[0059] Alignment refers to the one-to-one correspondence between color pixels and depth values ​​at the same position in the color image and depth map we obtain.

[0060] B. Perform segmentation preprocessing on color images;

[0061] The color image is segmented using the water ridge method to obtain all the segmented object areas of the color image, assuming that the segmented object area after the color image is segmented is (R 1 , R 2 ,...,R n ), wherein, n is the number of segmented object regions; image 3 shows the results of color im...

Embodiment 2

[0075] A kind of Kinect depth map restoration method based on color image segmentation as described in embodiment 1, difference is: the specific method of denoising described in step D is the method for guided filtering; With color image as guiding information, adopt guided filtering ( Guided filter) for filtering.

Embodiment 3

[0077] A Kinect depth map restoration method based on color image segmentation as described in Embodiment 1, the difference is that the specific method of denoising in step D is bilateral filtering.

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Abstract

The invention relates to a Kinect deep image remediation method based on colorful image segmentation. The Kinect deep image remediation method comprises the following steps: by taking a corresponding colorful image segmentation result as reference information for remedying a deep image, reconstructing an invalid area of the deep image, and furthermore by taking a colorful image as guidance information, filtering the reconstructed deep image, thereby achieving an effect of removing noise. Therefore, on the basis that reference information is provided through the simultaneously taken colorful images, the colorful images are segmented to obtain cavity reconstruction areas of the deep image, and a Kinect deep image with relatively good quality can be obtained.

Description

Technical field: [0001] The invention relates to a Kinect depth map restoration method based on color image segmentation, belonging to the technical field of image processing. Background technique: [0002] With the development of stereo display technology and video processing technology, depth map has become a research hotspot in stereo vision technology in recent years, and has been widely used in 3D reconstruction, 3D TV, depth image rendering (DIBR), image segmentation and many other fields. Depth maps can be obtained through stereo matching algorithms or depth cameras. The stereo matching algorithm is to determine the corresponding points of the pixels in the image pair acquired by the binocular camera to calculate the disparity map, and then convert it into a depth map according to the geometric relationship. Due to the high computational cost of such methods, most stereo matching methods cannot be used in practical applications. Depth cameras directly obtain depth i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T7/00
Inventor 陈辉李海坤
Owner 山东智瞰深鉴信息科技有限公司
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