Sparse representation depth image reconstruction algorithm based on structure dictionary

A sparse representation, depth image technology, applied in the field of image processing, can solve the problems of depth image noise, depth value, missing and so on

Active Publication Date: 2016-08-10
BEIJING UNIV OF TECH
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  • Sparse representation depth image reconstruction algorithm based on structure dictionary
  • Sparse representation depth image reconstruction algorithm based on structure dictionary
  • Sparse representation depth image reconstruction algorithm based on structure dictionary

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Embodiment

[0042] Explore the logical correspondence matrix Ω between the corresponding depth and the color image, specifically including:

[0043] 1) Sampling the corresponding depth and color images

[0044] Using the common sampling algorithm for the corresponding depth image Y 1 and color image Y 2 Sampling is performed separately to obtain the depth sample X 1 , color sample X 2 .

[0045] 2) Clustering depth samples

[0046] Since the present invention considers the depth and color images as a whole, after the sampling is completed, the depth and color samples are combined to obtain the overall sample X, namely According to the characteristics of the depth image, points on the same plane in the scene have the same depth information, it can be known that only a small amount of depth information in the sample can extract the features of the image. Therefore, according to the depth information in the overall sample, the general clustering algorithm (such as the K-Means algorith...

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Abstract

The invention discloses a sparse representation depth image reconstruction algorithm based on a structure dictionary, belonging to the image processing technology field. Firstly, the sparse representation depth image reconstruction algorithm of the invention considers a corresponding depth image and a corresponding color image as a whole, and, during the solution process, the sparse representation depth image reconstruction algorithm improves the reconstruction effect of the depth image and the color image through constructing a structure dictionary having a logic corresponding relation. During the dictionary construction process, the sparse representation depth image reconstruction algorithm based on the structure dictionary utilizes the logical corresponding relation between the depth image and the color image and the similarity relation of the depth image to improve the efficiency and quality of dictionary training. The depth image reconstruction algorithm combines the related theories like the sparse coding on the basis of collecting and arranging a lot of home and abroad related data, analyzes the correlation between data according to the close correlation between the depth image and the color image, mainly solves the reconstruction problem of the sparse representation depth image based on the structure dictionary, reduces the operation complexity, and improves the reconstruction quality of the depth image and the corresponding color image.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a sparse representation depth image reconstruction algorithm based on a structure dictionary. Background technique [0002] Sparse representation is a signal representation method, that is, a given signal can be reconstructed by a baseline sparse in a transform domain. The collection of bases in the transform domain is called a dictionary. In order to make the representation of the signal invariant to translation, the researchers introduced the concept of redundant representation, that is, the dimension of the representation coefficient of the signal in the transform domain is required to be larger than the dimension of the signal itself, that is, "over-complete". By looking for a set of "super-complete" basis vectors to represent the sample data more efficiently, a signal can be expressed as a linear combination of a set of basis vectors. Under the over-co...

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T2207/10024G06T2207/10028G06T2207/20081
Inventor 尹宝才尹海真施云惠丁文鹏
Owner BEIJING UNIV OF TECH
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