Multispectral image compression method and system based on multidirectional convolutional neural network
The invention discloses a multispectral image compression method and system based on a multidirectional convolutional neural network. The system comprises a forward coding network, a quantization module, an entropy coding module, an entropy decoding module, an inverse quantization module and a rever...
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| creator | CAO TONGBO KONG FANQIANG ZHANG NING HU KEDI |
| description | The invention discloses a multispectral image compression method and system based on a multidirectional convolutional neural network. The system comprises a forward coding network, a quantization module, an entropy coding module, an entropy decoding module, an inverse quantization module and a reverse decoding network. The method specifically comprises the following steps: constructing a multispectral image compression network and training the multispectral image compression network to obtain an optimal multispectral image compression network model; sending a to-be-compressed multispectral image into a multispectral image compression network, extracting inter-spectral spatial features of the image through multidirectional convolution, reducing the size of a feature map through downsampling after dimension reduction fusion, removing data redundancy through quantization, and obtaining a compressed code stream used for transmission and storage through lossless entropy coding; and performing entropy decoding and |
| format | Patent |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HANDLING RECORD CARRIERS IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
| title | Multispectral image compression method and system based on multidirectional convolutional neural network |
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