Form and color fused image super-resolution reconstruction model construction and reconstruction method
A technology of super-resolution reconstruction and construction method, which is applied in the field of image super-resolution reconstruction model construction and reconstruction that integrates shape and color, and can solve problems such as excessively smooth texture, blurred structure boundaries, and chaotic brightness and color.
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Embodiment 1
[0063] In this embodiment, a method for constructing an image super-resolution reconstruction model that fuses shape and color is disclosed, such as figure 1 shown, follow the steps below:
[0064] Step 1. Obtain multiple high-resolution images and obtain the target image set X, where X={X 1 ,X 2 ,...,X n ,...,X N},X n is the nth high-resolution image, N is a positive integer, n∈N;
[0065] Downsampling is performed on each high-resolution image to obtain multiple low-resolution images, and an image set x to be reconstructed is obtained, where x={x 1 ,x 2 ,...,x n ,...,x N}, x n is the nth low-resolution image;
[0066] In this embodiment, the model provided by the present invention is trained and tested using the training set and the test set, wherein the 1-800 high-resolution images in the DIV2K data set are down-sampled by a ratio of 4 to generate the corresponding low-resolution images images to construct a training dataset consisting of high / low resolution imag...
Embodiment 2
[0145] This embodiment discloses an image super-resolution reconstruction method that combines shape and color. After the image to be reconstructed is input into the image super-resolution reconstruction model described in Embodiment 1, a reconstructed image is obtained.
[0146] The following is the analysis of the experimental results of this experiment:
[0147] The comparative methods used in this experiment include: Bicubic, DRCN, VDSR, SRResNet, SRGAN-MSE, SRGAN, and EnhanceNet methods. figure 2 The SR reconstruction result of a low-resolution image is given, where (a) is the original HR image, (b) is the HR image obtained after bicubic interpolation of the LR image, (c) is the result of DRCN reconstruction, (d) is the result of VDSR, (e) is the reconstruction result of SRGAN, (f) is the reconstruction result of EnhanceNet, and (g) is the reconstruction result of the method of the present invention. As can be seen from the result figure, the super-resolution images obt...
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