Research on Image Compression of Packaging and Decoration Based on MATLAB (2)

For the same data, the uint8 format is more economical than the double format, saving memory space. In MATLAB, if the color image of the index image is less than 256 lines, its image matrix is ​​stored in uint8 format, otherwise it is stored in double format.
From the subjective evaluation of the recovered image, it can be seen that although the second compression ratio is greater than the first compression ratio, the first compression effect is significantly better than the second compression effect. This is because when the decomposition is performed, the increased number of decomposition layers will cause blurring at the edge of the baseband, which is not conducive to extracting the desired high frequency subband classification information or the extracted information is inaccurate, resulting in high frequency subbands. The effectiveness and rationality of the coding have declined.
4 Conclusion Image compression is a research field with promising future. The breakthrough in this field will have a profound impact on the development of packaging and printing. Therefore, invest a certain amount of funds and manpower in image compression to conduct in-depth research.
A1=wrcoef2('a',e,l,'dbl',1);
H1=wrcoef2('h',e,l,'dbl',1);
D1=wrcoef2('d',c,l,'dbl',1);
V1=wrcoef2('v',c,l,'dbl',1); c1=[A1 H1;V1 D1].
The following is the compression of the image: The first layer of low-frequency information is preserved and quantized and encoded. MATLAB uses the wcodemat() function to complete this process.
Cai=wcodemat(cAl,440,'that',0); cai=0.5*cal.
3 Experimental results and analysis The image used in this experiment is 256*256 pixels and each pixel is 8bit coded. The compression effect can be examined by comparing the memory space occupied by the original image lea and the compressed restored image and the displayed image, as shown in FIG. 1 .

It will help improve China’s international competitiveness in the field of high technology. The research and application of image compression algorithms have been very active over the years. Some foreign companies have applied this technology to the transmission of image data in the Internet environment and provided commercialized services. This has played a very good role in alleviating network bandwidth shortage and accelerating the speed of image information transmission. Digitization of graphic data will inevitably produce a large amount of image data, and the demand for high-rate image compression algorithms is particularly urgent. As an excellent image compression algorithm, the wavelet transform of MATLAB tool has a very good application prospect in this field, and it should also be able to play a key role. At the same time, it will surely promote the application of this technology in China. Powerful role.