Super-resolution reconstruction method for depth map by adopting autoregressive model

A super-resolution reconstruction and autoregressive model technology, applied in the field of computer vision, can solve problems such as small structure confusion and inability to maintain edge sharpness

Active Publication Date: 2012-10-10
TIANJIN UNIV
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Problems solved by technology

However, none of the methods mentioned above can maintain the sharpness of the edges very well, and it is also easy to cause confusion on small structures.

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  • Super-resolution reconstruction method for depth map by adopting autoregressive model
  • Super-resolution reconstruction method for depth map by adopting autoregressive model
  • Super-resolution reconstruction method for depth map by adopting autoregressive model

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Embodiment Construction

[0045] The autoregressive model-based depth map super-resolution of the present invention will be described in detail below with reference to the embodiments and the accompanying drawings.

[0046] The present invention uses the autoregressive model to perform super-resolution reconstruction on the depth map: the depth map super-resolution problem is specifically expressed as an autoregressive model solution equation, and the alignment is performed by 1) using a bilateral filter kernel to replace the non-mean filter of the Gaussian kernel The color image of the autoregressive model is trained with color-guided coefficients 2) The bicubic interpolation method is used to guide the depth map of the original low-resolution interpolation with blurred boundaries, and the coefficient training of the autoregressive model is performed again, and the two parts The obtained coefficients are multiplied and brought into the solution equation as the final model coefficients and optimized. T...

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Abstract

The invention belongs to the field of computer vision. In order to provide a simple and practical super-resolution method, the technical scheme adopted by the invention is that a super-resolution reconstruction method for a depth map by adopting an autoregressive model comprises the following steps of: 1) taking the depth map and a color map which are provided by a Middlebury data set and has the same size as experimental data, performing down-sampling on a test depth map according to a super-resolution proportion, performing zero-fill up-sampling on the obtained input low-resolution depth map to the original resolution, and obtaining an initial depth scatter diagram; 2) constructing autoregressive model items of an energy function; 3) constructing basic data items and a final solving equation of the energy function; and 4) solving the equation b utilizing a linear function optimization method. The super-resolution reconstruction method is mainly used for image processing.

Description

technical field [0001] The invention belongs to the field of computer vision and relates to a method for super-resolutioning a low-resolution depth map by using an autoregressive model with a predictive effect. Specifically, it involves deep super-resolution reconstruction methods based on autoregressive models. Background technique [0002] Super-resolution (Super-Resolution) is to improve the resolution of the original image through hardware or software methods, and use low-resolution images to obtain high-resolution images. The core idea of ​​super-resolution reconstruction is to exchange temporal bandwidth (obtain multi-frame image sequences of the same scene) for spatial resolution, and realize the conversion from temporal resolution to spatial resolution. [0003] With the advancement of imaging technology, depth cameras launched in recent years have broken through the limitations of traditional laser scanning and stereo matching for depth imaging, and can easily obta...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 杨敬钰叶昕辰侯春萍李坤
Owner TIANJIN UNIV
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