A Method of Image Compression Based on Huffman Coding

Abstract

The invention discloses an image compression method based on Huffman coding, belonging to the technical field of digital image processing. The method includes the following steps: reading an image, and parsing the image to acquire image information; carrying out image segmentation processing; carrying out image processing on the segmented sub-images to generate an updated image of which the offsetis replaced; traversing the entire image, and performing probability statistics to obtain the offset of all pixel points of the entire image except a central reference pixel point; establishing a Huffman binary tree, obtaining a Huffman code, and storing the code in a cell array; performing table look-up on the updated image of which the offset is replaced according to a Huffman code table to obtain a variable-length Huffman code corresponding to the offset, and storing the Huffman code corresponding to the offset in a cell array that has the same size as the original image; performing reverse table look-up to generate original images of three channels R, G and B; and synthesizing the generated original images of three channels R, G and B to restore the original image. According to the scheme of the invention, the image space redundancy can be reduced, and the image lossless compression and recovery can be achieved.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, in particular to an image compression method based on Huffman coding. Background technique [0002] With consumers' pursuit of high-quality images, the pixels of image acquisition devices are getting higher and higher, which poses great challenges to image storage, transmission, and processing. Therefore, image compression technology has become a hot research field. The significance of image compression is to reduce the amount of data storage and save storage space; reduce the data rate to reduce the bandwidth used during transmission and save transmission time; compress the information of the image to facilitate feature extraction. [0003] At present, the industry compresses and encodes images based on the visual characteristics of the human eye and the spatial and temporal characteristics of images to reduce the amount of image data. However, common compression methods have l...

AI Technical Summary

Problems solved by technology

[0004] Image compression methods such as JPG and PNG have high compression efficiency, but due to the use of spatial frequency domain changes, the loss of low-frequency information is large, and the information of the original image data is less reserved, so it is not suitable for the restoration of the original image.

[0005] JPEG2000 lossless compression method, the process is complicated, and the implementation method is complicated

[0006] The common video compression coding (H264 / MPEG) uses a variety of compression algorithms in the space domain and time domain to realize the compression of real-time video images, but the loss of image information is large, which is not suitable for the restoration of the original image

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