Convolutional neural network image super-resolution reconstruction method fused with bionic vision mechanism

A technology of super-resolution reconstruction and convolutional neural network, which is applied in the field of image processing, can solve the problems of reducing processing speed and large format of remote sensing images, and achieve the effects of improving efficiency, speeding up reconstruction speed, and ensuring reconstruction quality

Active Publication Date: 2020-06-26
NANJING UNIV OF SCI & TECH
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Problems solved by technology

[0003] The remote sensing image has a large format and contains a lot of information. If the entire remote sensing image is directly processed, the processing speed will be greatly reduced.

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  • Convolutional neural network image super-resolution reconstruction method fused with bionic vision mechanism
  • Convolutional neural network image super-resolution reconstruction method fused with bionic vision mechanism
  • Convolutional neural network image super-resolution reconstruction method fused with bionic vision mechanism

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Embodiment

[0075] This embodiment is based on configuration: Intel Core I7 1050CPU, personal PC with memory 16G, operating system is Windows 10 (x64), and simulation software is MATLAB R2016b. Figure 2(a) ~ Figure 2(e) Some experimental results are given, which are parking lots, parking aprons, road breaks, large ports, and road turntables. The first column is the low-resolution image, the second column is the salient map, the third column is the salient area, and the fourth column is the salient area. Listed as the reconstructed image. For a clearer display, we zoomed in on the details of the images before and after reconstruction in the group of Figure 2(b), as shown in image 3 As shown, the left picture is before reconstruction, and the right picture is after reconstruction. It can be seen from the results that the algorithm of the present invention achieves good visual effects subjectively.

[0076] Comparing the algorithm proposed by the present invention with the existing convo...

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Abstract

The invention discloses a convolutional neural network image super-resolution reconstruction method fused with a bionic vision mechanism, and the method comprises the steps: firstly carrying out the saliency region detection of a remote sensing image through employing a saliency detection method for simulating a human vision attention mechanism; secondly, for the salient region, performing super-resolution reconstruction by adopting an image super-resolution reconstruction method based on a convolutional neural network; and finally, carrying out super-resolution reconstruction on the non-salient region by adopting a bicubic interpolation method. Compared with an existing image super-resolution reconstruction method based on a convolutional neural network, the method provided by the invention can quickly perform super-resolution reconstruction on the image, and is suitable for occasions with strict real-time requirements.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to a convolutional neural network image super-resolution reconstruction method integrated with a bionic vision mechanism. Background technique [0002] In real life, the hardware conditions of various imaging instruments have great limitations, and the resolution of the obtained images often cannot meet the actual needs. And only by improving hardware conditions in order to obtain high resolution, the cost is expensive. Therefore, it is necessary to study the method of improving resolution through software. Image super-resolution reconstruction refers to using software to reconstruct an image based on one or more images with lower resolution. The resolution of this image is significantly higher than that of the original image. [0003] The remote sensing image has a large format and contains a lot of information. If the entire remote sensing image is processed directly,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40G06N3/04
CPCG06T3/4053G06T3/4007G06N3/045
Inventor 王鑫王琼
Owner NANJING UNIV OF SCI & TECH
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