Image encoding and decoding method and device based on wavelet transform

Abstract

The invention discloses an image encoding and decoding technology in the field of computers, and particularly relates to an image encoding and decoding method based on wavelet transform, and the method comprises the following steps: during encoding, performing wavelet transform on an image to be encoded for N times according to a wavelet transform model to obtain a wavelet coefficient, wherein thewavelet transform model is realized based on a CNN; quantizing the wavelet coefficients, so as to obtain a quantized wavelet coefficient; carrying out the entropy coding on the quantized wavelet coefficient to obtain a compressed code stream; during decoding, carrying out the entropy decoding on the compressed code stream to obtain a reconstructed wavelet coefficient; carrying out the inverse quantization on the reconstructed wavelet coefficient to obtain an inverse quantized wavelet coefficient; according to a wavelet transformation model, carrying out the wavelet inverse transformation on the wavelet coefficient after inverse quantization for N times to obtain a reconstructed image, wherein the wavelet transformation model is realized based on the CNN. By adopting the embodiment of theinvention, the coding and decoding performance of the image can be improved.

Description

technical field [0001] The invention relates to the field of image encoding and decoding, in particular to an image encoding and decoding method and device based on wavelet transform. Background technique [0002] Digital images are image information recorded in the form of digital signals. A digital image (hereinafter referred to as an image) can be regarded as a two-dimensional array of M rows and N columns, including M×N samples, the position of each sample is called a sampling position, and the value of each sample is called a sample value. [0003] In applications such as image storage and transmission, it is usually necessary to encode images to reduce storage capacity and transmission bandwidth. A typical image coding process generally includes three steps of transformation, quantization and entropy coding. For an image to be encoded, the first step is to decorrelate the image to be encoded by transforming to obtain the transformation coefficient with more concentra...

AI Technical Summary

Problems solved by technology

Although the adaptive directional wavelet can adaptively select the wavelet basis function of the corresponding direction according to the directional characteristics of the image itself, it overcomes the disadvantage that the directional wavelet can only use a limited number of basis functions.

However, the direction parameter selection based on block division relies on multiple encoding decision-making processes, which greatly increases the encoding complexity

At the same time, adaptive directional wavelet still has not resolved the contradiction between the diversity and complexity of natural image features and the ideality and simplicity of artificially designed wavelet basis functions.

[0008] In summary, the image encoding and decoding efficiency of the current technology is low, and it cannot solve the contradiction between the diversity and complexity of natural image features and the ideality and simplicity of artificially designed wavelet basis functions.

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