不同有损图像压缩技术的比较

Y. L. Prasanna, Y. Tarakaram, Y. Mounika, R. Subramani
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引用次数: 4

摘要

近年来,大量图像数据在互联网等应用程序中的使用迅速增加。因此,为了有效地利用网络的存储空间和带宽,就需要对图像进行压缩。我们有两种图像压缩——一种是有损图像压缩,另一种是无损图像压缩。有损图像压缩产生一种压缩图像,其中图像的质量保持在一些数据丢失的情况下。与无损压缩相比,有损压缩得到了广泛的应用。在这里,使用三种有损图像压缩技术-离散余弦变换(DCT),奇异值分解(SVD)和离散小波变换(DWT)进行图像压缩。使用峰值信噪比(PSNR)、压缩比(CR)、结构相似指数测量(SSIM)和均方误差(MSE)等性能指标对这些技术进行了比较。
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Comparison of Different Lossy Image Compression Techniques
Recently, the use of large volumes of image data in many applications like internet has been increasing rapidly. So, to make an effective use of storage space and also bandwidth of the network, image compression is required. We have two kinds of image compression - one is lossy and other is lossless image compression. Lossy image compression produces a compressed image where quality of the image is maintained with some data loss. Lossy compression is widely used compared to lossless compression. Here, three lossy image compression techniques - Discrete Cosine Transform(DCT), Singular Value Decomposition (SVD) and Discrete Wavelet Transform(DWT) are used to perform image compression. These techniques are compared using some performance measures such as Peak Signal-to- Noise Ratio(PSNR), Compression Ratio(CR), Structural Similarity Index Measure(SSIM) and Mean Square Error(MSE).
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