Description: 输入:为需要压缩图象的名称,该主程序仅能构处理256灰度图,读者可以自行改编为RGB处理;ratio为压缩比率;level为小波分解的级数
输出:是解压完毕的图象数据矩阵-input : the need for image compression name, the main program can only handle 256 gray level structure, Readers can own adaptation of RGB; ratio of compression ratio; wavelet decomposition level for the series output : is finished unpacking the image data matrix Platform: |
Size: 54272 |
Author:林颖 |
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Description: matlab图象处理中非常有用的程序,RGB图象转化为灰度图象的程序,在运用中很有效-Matlab image processing is very useful procedure, RGB images into gray-scale images procedures, in the use of very effective Platform: |
Size: 1024 |
Author:李里 |
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Description: dctcom.m文件利用DCT变换完成对输入图像进行压缩;imagecbe.m完成对输入的两幅RGB图像用小波分析的方法进行图像融合 imagecom.m完成对输入的RGB图像用小波分析的方法进行自动降噪,得到高频系数阈值,降噪效果百分比和结果 wavelet1D.m完成对输入的一维信号进行多尺度离散小波分解 wavelet2D完成对输入的二维信号进行多尺度离散小波分解;zigzag.m完成对输入的8*8矩阵按照zigzag排列抽取数据.-document the use of DCT transform dctcom.m completion of the input image compression imagecbe.m completion of the two RGB input image with wavelet analysis method of image fusion imagecom.m completion of the input RGB image using wavelet analysis method automatically drop noise, the threshold of high-frequency coefficient, noise reduction effect and the results of the percentage of wavelet1D.m completion of the input signals of one-dimensional discrete wavelet multi-scale decomposition wavelet2D completion of the input signals of two-dimensional discrete wavelet multi-scale decomposition zigzag.m completed the input of 8* 8 matrix of data collected in accordance with the zigzag order. Platform: |
Size: 3072 |
Author:zhouhao |
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Description: The following implementation steps have been made for the devised algorithm, which is based on 2D-wavelet.
1. Reading an image of either gray scale or RGB image.
2. Converting the image into grayscale if the image is RGB.
3. Decomposition of images using wavelets for the level N.
4. Selecting and assigning a wavelet for compression.
5. Generating threshold coefficients using Birge-Massart strategy.
6. Performing the image compression using wavelets.
7. Computing and displaying the results such as compressed image, retained energy and Zero coefficients.
8. Decompression the image based on the wavelet decomposition structure.
9. Plotting the reconstructed image.
10. Computing and displaying the size of original image, compressed image and decompressed image. Platform: |
Size: 1024 |
Author:fer |
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