Light field image multi-magnification spatial super-resolution method and device

Abstract

The invention discloses a light field image multi-magnification spatial super-resolution method and device. The method comprises the following steps: S1, training a single-image super-resolution network based on an EDSR structure; s2, using the trained single-image super-resolution network model to carry out single-image super-resolution with the magnification of m on all view angle images of the low-spatial-resolution light field image; s3, extracting a polar plane image before restoration from a single-image super-resolution result to form a polar plane image cube; s4, constructing a U-shaped polar plane image cube multi-magnification repair network based on an attention residual structure; s5, training the multi-magnification repair network of the polar plane image cube, repairing the information of the polar plane image cube by using the trained network model, and obtaining the polar plane image cube in which the geometric continuity of the space target in the visual angle dimension is recovered; and S6, reconstructing the repaired polar plane image cube into a light field image space super-resolution result with the multiplying power of m. According to the method provided by the invention, the super-resolution effect of the network is improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method and device for multi-magnification spatial super-resolution of light field images. Background technique [0002] Light field imaging technology can capture light direction information, and obtain multi-view images of space scenes by taking a single photo. Compared with traditional imaging technology, light field imaging technology can not only obtain the position information and light intensity information of objects in the scene on the detector, The angle information of the light rays can also be obtained. Therefore, light-field cameras have advantages in tasks such as depth estimation and post-capture refocusing. [0003] In the case of generalized focusing of a light field camera based on a microlens array, the product of the viewing angle resolution and the spatial resolution cannot exceed the resolution of the camera sensor. However, the number of detecto...

AI Technical Summary

Problems solved by technology

However, on the one hand, the existing learning-based light field image space super-resolution algorithms need to retrain the network parameters for different magnifications; The problem that the distribution of spatial information on the two perspective dimensions cannot be fully considered when the network is trained on the object

In summary, there is room for improvement in the above technologies

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