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Image compression using discrete cosine transform and discrete wavelet transform

机译:使用离散余弦变换和离散小波变换的图像压缩

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摘要

It is used specially for the compression of images where tolerable degradation is required. With the wide use of computers and consequently need for large scale storage and transmission of data, efficient ways of storing of data have become necessary. With the growth of technology and entrance into the Digital Age ,the world has found itself amid a vast amount of information. Dealing with such enormous information can often present difficulties. Image compression is minimizing the size in bytes of a graphics file without degrading the quality of the image to an unacceptable level. The reduction in file size allows more images to be stored in a given amount of disk or memory space. It also reduces the time required for images to be sent over the Internet or downloaded from Web pages.JPEG and JPEG 2000 are two important techniques used for image compression. JPEG image compression standard use DCT (DISCRETE COSINE TRANSFORM). The discrete cosine transform is a fast transform. It is a widely used and robust method for image compression. It has excellent compaction for highly correlated data.DCT has fixed basis images DCT gives good compromise between information packing ability and computational complexity. JPEG 2000 image compression standard makes use of DWT (DISCRETE WAVELET TRANSFORM). DWT can be used to reduce the image size without losing much of the resolutions computed and values less than a pre-specified threshold are discarded. Thus it reduces the amount of memory required to represent given image.
机译:它专门用于需要可容忍降级的图像压缩。随着计算机的广泛使用以及因此对大规模存储和数据传输的需求,已经需要有效的数据存储方式。随着技术的发展和进入数字时代,世界已经在大量信息中找到了自己。处理如此大量的信息通常会带来困难。图像压缩可最大程度地减小图形文件的字节大小,而不会降低图像质量到不可接受的水平。文件大小的减小允许在给定数量的磁盘或内存空间中存储更多图像。它还减少了图像通过Internet发送或从网页下载所需的时间。JPEG和JPEG 2000是用于图像压缩的两项重要技术。 JPEG图像压缩标准使用DCT(DISCRETE COSINE TRANSFORM)。离散余弦变换是一种快速变换。它是一种广泛使用且健壮的图像压缩方法。 DCT具有固定的基础图像DCT在信息打包能力和计算复杂性之间取得了很好的折衷。 JPEG 2000图像压缩标准利用了DWT(离散小波变换)。 DWT可用于减小图像大小,而不会丢失许多计算出的分辨率,并且会丢弃小于预定阈值的值。因此,它减少了表示给定图像所需的内存量。

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    Bhawna Gauatm;

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  • 年度 2010
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