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Method for fusing full-color image and multispectral image based on deep neural network

A deep neural network and multi-spectral image technology, applied in image enhancement, image conversion, image data processing, etc., can solve problems such as non-linear description of remote sensing image structure information, achieve high spatial resolution, improve quality, and preserve The effect of spectral information

Active Publication Date: 2014-10-22
NANJING UNIV OF SCI & TECH
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Problems solved by technology

Although these methods can reconstruct high-resolution multispectral images well, they only share a shallow linear structure and cannot describe the complex structural information of remote sensing images nonlinearly.

Method used

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  • Method for fusing full-color image and multispectral image based on deep neural network
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  • Method for fusing full-color image and multispectral image based on deep neural network

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Embodiment 1

[0057] combine figure 1 , a method for fusion of panchromatic images and multispectral images based on deep neural networks, the specific steps are as follows:

[0058] Step 1. Construct a training set paired with high-resolution and low-resolution image patches The specific process is:

[0059] Step 1.1, multispectral images of known low spatial resolution Perform a band-by-band interpolation operation, zoom in 4 times to get an initially enlarged multispectral image in Contains 4 bands, the pixel size of each band image is 150×150, It also contains 4 bands, and the pixel size of each band image is 600×600;

[0060] Step 1.2, for known high-resolution panchromatic images with a size of 600×600 and the initial upscaled multispectral image The maximum and minimum normalization method is performed on each band pixel, so that their pixel value range is between [0,1]. Among them, the high-resolution panchromatic image Such as Figure 4 As shown in (a), the image ...

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Abstract

The invention provides a method for fusing a full-color image and a multispectral image based on a deep neural network. Specific steps are as follows: step 1. constructing a training set of high resolution and low resolution image block pairs; step 2. using an improved sparse denoising self-encoder to learn to train initialization parameters of a first layer in a neural network model; step 3. using the improved sparse denoising self-encoder to perform pretraining of the neural network layer by layer; step 4. performing fine adjustment of parameters of the pretrained deep neural network; and step 5. using the deep neural network to reconstruct a multispectral image of high resolution according to a known multispectral image of low spatial resolution. The method provided by the invention adopts a method of deep learning, and can make full use of a nonlinear neural network to depict complex structural information of a multispectral image, thereby enabling the fused multispectral image to have high spatial resolution, and well keeping spectral information of the multispectral image.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and in particular relates to a high-resolution panchromatic image and multispectral image fusion method based on a deep neural network. Background technique [0002] Earth observation satellites typically provide two different types of imagery, panchromatic images with high spatial and low spectral resolution and multispectral images with low spatial and high spectral resolution. Currently, it is generally difficult to directly acquire highly spatially and hyperspectral-resolved multispectral images due to the technical limitations of current satellite sensors. Therefore, it is undoubtedly a better choice to obtain high-spatial and hyperspectral-resolved multispectral images through a technology that fuses information from these two different types of images. [0003] The method of multispectral image fusion is to fuse the panchromatic image with high spatial resolution a...

Claims

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Application Information

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IPC IPC(8): G06T5/50G06T3/40G06K9/66
Inventor 黄伟肖亮韦志辉
Owner NANJING UNIV OF SCI & TECH
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