Sparse matrix and convolutional neural network-based picture compression method

A technology of convolutional neural network and sparse matrix, which is applied to the image compression of neural network. Based on the field of sparse matrix, it can solve the problems of small quality degradation, difficult to use and identify, and no compression ratio, etc., to achieve good effect and less distortion. Effect

A technology of convolutional neural network and sparse matrix, which is applied to the image compression of neural network. Based on the field of sparse matrix, it can solve the problems of small quality degradation, difficult to use and identify, and no compression ratio, etc., to achieve good effect and less distortion. Effect

CN107301668AActive Publication Date: 2017-10-27CHENGDU SEFON SOFTWARE CO LTD
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  • Sparse matrix and convolutional neural network-based picture compression method
  • Sparse matrix and convolutional neural network-based picture compression method
  • Sparse matrix and convolutional neural network-based picture compression method

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Embodiment 1

[0071] A picture compression method based on a sparse matrix and a neural network, which includes a picture compression process and a picture restoration process.

[0072] Such as figure 1 , a kind of picture compression method based on sparse matrix, neural network, described picture compression method comprises the following steps:

[0073] S1: Use the neural network to evaluate and optimize the image sparse matrix, and construct the optimal sparse matrix;

[0074] S2: Use the neural network to select the optimal compression algorithm and compress the image sparse matrix to obtain the compressed image;

[0075] Wherein, the evaluation, optimization and construction of the image sparse matrix include the following sub-steps:

[0076] S11: converting the image to be compressed into two-dimensional matrix data;

[0077] S12: Using a neural network to process the two-dimensional matrix data to obtain a candidate image sparse matrix;

[0078] S13: Evaluate the constructed can...

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Abstract

The invention discloses a sparse matrix and convolutional neural network-based picture compression method. The method comprises the following steps of converting an image into two-dimensional matrix data; assessing, optimizing and constructing a sparse matrix image by utilizing a convolutional neural network; optimizing a compression scheme through the convolutional neural network; performing compression processing on the sparse matrix image by using the selected optimal compression scheme; and finally obtaining a high-compression-ratio and low-distortion compressed image. According to the method, the problem of difficult use and identification of the image due to low compression ratio and excessively reduced quality of the compressed image in an existing compression technology is solved; and the optimization can be carried out according to picture contents, and the proper image construction and compression method can be self-selected, so that the picture feature extraction and compression method has self-optimization and learning capabilities.

Description

technical field [0001] The invention relates to the technical field of picture processing, in particular to a picture compression method based on a sparse matrix and a neural network. Background technique [0002] Image compression technology is an important technical field in image processing technology. Image compression can effectively reduce file size, save storage space, and reduce network transmission pressure. [0003] At present, the common compression technologies include JPG, PNG, RAR, etc. JPG, PNG and other algorithms are specially designed for image format file compression, which can compress the original bitmap to 10%-70% of the size, and have been widely used in the computer industry. , the operating system and application software usually use these algorithms as the general standards supported by default, but the disadvantage is that these two algorithms will have different degrees of quality loss according to different compression ratios. RAR and other tech...

Claims

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Application Information

Patent Timeline
27 Oct 2017
Publication
CN107301668A
IPC
G06T9/00; G06N3/02
CPC
G06N3/02; G06T9/00
Inventors
蓝科; ηŽ‹ηΊ―ζ–Œ