JPG, PNG and BMP image compression using discrete cosine transform
JPG, PNG and BMP image compression using discrete cosine transform
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使用离散余弦变换压缩 JPG、PNG 和 BMP 图像
DOI：
10.12928/telkomnika.v19i3.14758
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发表时间：
2021
影响因子：
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通讯作者：
K. A. Aziz
中科院分区：
文献类型：
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作者：
R. A. Hamzah;Muttaqin Md Roslan;A. F. Kadmin;S. F. A. Gani;K. A. Aziz
提出了一种基于离散余弦变换(DCT)的联合图像专家组(JPG)或JPG、便携式网络图形(PNG)和位图(BMP)格式的图像压缩方法。这三种扩展是当前图像处理存储中最常用的类型。图像压缩的目的是产生较低的内存使用量或减少内存文件。该过程去除了每个像素的冗余信息。图像压缩过程面临的挑战是如何在压缩后保持图像的质量。因此，本文利用离散余弦变换技术在保持图像质量的同时减小了图像的存储容量。DCT技术在一些真实图像上的有效性是合理的，并且该技术的实现已经与不同类型的图像扩展进行了比较。MatLab软件是本项目的重要平台，为了编写程序，分阶段执行项目进度，达到预期效果。基于测试图像，DCT技术在图像压缩中能够平均减少每幅测试图像约50%的图像存储空间。
This paper proposes image compression using discrete cosine transform (DCT) for the format of joint photographic expert groups (JPEG) or JPG, portable network graphic (PNG) and bitmap (BMP). These three extensions are the most popular types used in current image processing storage. The purpose of image compression is to produce lower memory usage or to reduce memory file. This process removes redundant information of each pixel. The challenge for image compression process is to maintain the quality of images after the compression process. Hence, this article utilizes the DCT technique to sustain the image quality and at the same time reduces the image storage size. The effectiveness of the DCT technique has been reasonable over some real images and the implementation of the technique has been compared with different types of image extensions. Matlab software is an important platform for this project in order to write a program and perform the progress of project phase by phase to achieve the expected results. Based on the tested images, the DCT technique in image compression is capable to reduce the image storage memory in average about 50% of each image tested.