Still image compression method based on deep convolutional neural network

Abstract

The invention discloses a still image compression method based on a deep convolutional neural network. The still image compression method mainly comprises the following steps of: carrying out downsampling on an original image at an encoding end and carrying out encoding and decoding by utilizing a JPEG2000 standard; carrying out an inhibition compression effect on a decoded image by utilizing the deep convolutional neural network; reconstructing an inhibition compression effect image by adopting a super-resolution method; carrying out subtraction on the original image and a decoded high-resolution image to obtain a residue image and carrying out targeted encoding; forming bit stream by an encoded low-resolution image, the residual image and auxiliary information and transmitting the bit stream; carrying out decoding by a decoding end to obtain a decoded low-resolution image, residual image and auxiliary information; and processing the decoded low-resolution image to obtain a decoded high-resolution image, carrying out superposition on the decoded high-resolution image and the decoded residual image to obtain a finally decoded high-resolution image. The still image compression method disclosed by the invention has higher rate distortion performance than the JPEG2000 standard.

Description

technical field [0001] The invention relates to image compression and image super-resolution reconstruction technology, in particular to a still image compression method based on a deep convolutional neural network, which belongs to the field of image communication. Background technique [0002] The purpose of image compression is to store and compress more efficiently. As one of the basic technologies in the image field, image compression has always been concerned by researchers. With the popularization of high-resolution images and videos, image compression technology becomes more important. The JPEG2000 standard is an image compression technology based on discrete wavelet transform, which has better compression performance than the JPEG standard. However, in the case of medium and low bit rates, JPEG2000 standard decoding images have serious jagged and ringing effects, which seriously affect people's subjective visual effects. [0003] Image super-resolution reconstruc...

AI Technical Summary

Problems solved by technology

However, in the case of medium and low bit rates, JPEG2000 standard decoding images have serious jagged and ringing effects, which seriously affect people's subjective visual effects.

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