Description: 介绍了JPEG图像压缩算法,并在MATLAB 数学分析工具环境下从实验角度出发,
较为直观地探讨了DCT 在JPEG图像压缩中的应用。仿真实验表明,用MATLAB 来实现离散余弦
变换的图像压缩,具有方法简单、速度快、误差小的优点,大大提高了图像压缩的效率和精度。
李秀敏1 , 万里青1 , 周拥军2
(1. 河南科技大学电子信息工程学院,河南洛阳 471003 2. 中航一集团洛阳电光设备研究所,河南洛阳 471009)-introduced the JPEG image compression algorithm, MATLAB and mathematical analysis tool environment from experimental perspective, more directly on the DCT in JPEG image compression applications. Simulation results show that the use MATLAB to achieve discrete cosine transform image compression method is simple, fast, the advantages of a small error, which has greatly enhanced the efficiency of image compression and accuracy. LI Xiu-1, Green 1 Wanli, Zhou Yongjun 2 (1. Henan University of Science and Technology of Electronics and Information Engineering College, Luoyang, Henan 471003 2. A350 Luoyang Electro-Optic Equipment Institute, Luoyang, Henan 471009) Platform: |
Size: 108544 |
Author:adnsid |
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Description: 这是我做的毕业设计，是基于DSP的数字图象压缩系统的实现。本系统能很好的压缩图象，系统运行时间快，压缩比也比较高。其中采用JPEG标准对图象进行压缩，使用了Huffman算法。-This is what I am doing graduate design is based on the DSP digital image compression system is achieved. The system can be a very good image compression, faster system running time, the compression ratio is relatively high. Which use JPEG standard for image compression, the use of the Huffman algorithm. Platform: |
Size: 322560 |
Author:高燕 |
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Description: 提出一种基于视觉特性的图像摘要算法，增大人眼敏感的频域系数在计算图像Hash时的权重，使得图像Hash更好地体现视觉特征，并提高鲁棒性。将原始图像的分块DCT系数乘以若干由密钥控制生成的伪随机矩阵，再对计算的结果进行基于分块的Watson人眼视觉特性处理，最后进行量化判决产生固定长度的图像Hash序列。本算法比未采用视觉特性的算法相比，提高了对JPEG压缩和高斯滤波的鲁棒性。图像摘要序列由密钥控制生成，具有安全性。-Based on the visual characteristics of the image digest algorithm, increasing the human eye-sensitive frequency-domain coefficients in the calculation of the image when the weight of Hash, Hash makes images better reflect the visual characteristics, and improve robustness. Will block the original image multiplied by the number of DCT coefficients generated by the key control of pseudo-random matrix, then the results of calculation based on the sub-block of Watson HVS treatment, and finally quantify the judgments arising from fixed-length sequence of images Hash . Than the algorithm did not use the visual characteristics of the algorithm, improve the JPEG compression and Gaussian filtering robustness. Abstract image sequence generated by the key control, with security. Platform: |
Size: 167936 |
Author:kurt |
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Description: 一个简单对图象进行JPEG图像压缩算法。希望对大家有所帮助-A simple image to JPEG image compression algorithm. I hope all of you to help Platform: |
Size: 1024 |
Author:yangmengling |
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Description: 非常好且全面的jpeg图像压缩算法，jpeg压缩编码标准及其源码希望对大家有所帮助。-Very good and comprehensive jpeg image compression algorithm, jpeg compression coding standard and its source would like to help everyone. Platform: |
Size: 16540672 |
Author:乔鹏飞 |
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Description: 有关图像压缩的jpeg实现算法介绍及其源码-Related to the jpeg image compression algorithm introduced and its source Platform: |
Size: 162816 |
Author:刘荣国 |
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Description: 完整详尽的用C语言实现图像的JPEG压缩算法.-Integrity of the C language with a detailed realization of the JPEG image compression algorithm. Platform: |
Size: 327680 |
Author:沧海一笑 |
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Description: DCT and Image Compression
In the JPEG image compression algorithm, the input image is divided into
8-by-8 or 16-by-16 blocks, and the two-dimensional DCT is computed for each
block. The DCT coefficients are then quantized, coded, and transmitted. The
JPEG receiver (or JPEG file reader) decodes the quantized DCT coefficients,
computes the inverse two-dimensional DCT of each block, and then puts the
blocks back together into a single image. For typical images, many of the
DCT coefficients have values close to zero these coefficients can be discarded
without seriously affecting the quality of the reconstructed image.
The example code below computes the two-dimensional DCT of 8-by-8 blocks
in the input image, discards (sets to zero) all but 10 of the 64 DCT coefficients
in each block, and then reconstructs the image using the two-dimensional
inverse DCT of each block. The transform matrix computation method is used.- DCT and Image Compression
In the JPEG image compression algorithm, the input image is divided into
8-by-8 or 16-by-16 blocks, and the two-dimensional DCT is computed for each
block. The DCT coefficients are then quantized, coded, and transmitted. The
JPEG receiver (or JPEG file reader) decodes the quantized DCT coefficients,
computes the inverse two-dimensional DCT of each block, and then puts the
blocks back together into a single image. For typical images, many of the
DCT coefficients have values close to zero these coefficients can be discarded
without seriously affecting the quality of the reconstructed image.
The example code below computes the two-dimensional DCT of 8-by-8 blocks
in the input image, discards (sets to zero) all but 10 of the 64 DCT coefficients
in each block, and then reconstructs the image using the two-dimensional
inverse DCT of each block. The transform matrix computation method is used. Platform: |
Size: 1024 |
Author:Eldhose |
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Search - jpeg image compression algorithm