Image compression method based on optical contourlet transformation

Abstract

The invention discloses an image compression method based on the optical contourlet transformation. The image compression method comprises the following steps that S1, an image signal is acquired; S2, a sparse matrix of the image signal is acquired by adopting the optical contourlet transformation; S3, a gaussian random matrix is adopted to serve as a measurement matrix; S4, the sparse matrix and the measurement matrix are subjected to parallel multiplication calculation to acquire a compression signal; and S5, the compression signal is subjected to decompression and image reconstruction by using an orthogonal matching pursuit algorithm in a greedy algorithm. According to the method, the optical contourlet transformation is applied to compression encoding of an image or a video; the parallel multiplication calculation of the sparse matrix and the measurement matrix is achieved by adopting FPGA (field programmable gate array) parallel multiplication calculation and by combining the optical contourlet transformation with a compressive sensing theory; and a real-time processing function is achieved. An optical technology and an electrical system are applied in the method to achieve the optical contourlet transformation. Based on the responsiveness, the interconnection and paralleling capacity, and the storage capacity of the optical technology, the signals can be reconstructed more quickly and accurately by using photon as a carrier to store, send and process information.

Description

Technical field [0001] The invention relates to the field of image and video compression, in particular to a novel image compression method based on optical contour wave transformation. Background technique [0002] With the development of information network, people's demand for image storage and communication is increasing, and the amount of data is also increasing. Image compression technology becomes more and more important. Image compression mainly includes three parts: transformation, quantization, and entropy coding. The main functions are to decorrelate, further reduce the amount of data, and express with binary coding. Image compression originated in the 1920s. The theory of the first generation of image coding technology (represented by JPEG) was based on information theory and digital signal processing technology, with the purpose of removing the linear correlation in image data, and was limited by the current Technology, the ability to remove redundant information is...

AI Technical Summary

Problems solved by technology

[0004] Disadvantages: The current image compression coding technology has disadvantages such as geometric distortion, loss of high-frequency parts, block effect, difficulty in real-time compression, large amount of search and matching, and image distortion.

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