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Satellite Image Compression Using DCT Technique

机译:使用DCT技术压缩卫星图像压缩

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摘要

Compression of an image forms the indivisible part of the digital image storage and transmission. The limitation of storage and bandwidth capacity brings the necessity for image compression. Discrete Cosine Transform (DCT) is the technique used here for converting spatial components into frequency component. An algorithm is developed to compute DCT that yields compression of image. Compressed image is decompressed using Inverse Discrete Cosine Transformed (IDCT) to obtain a reconstructed image. The compression ratio (CR), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) are computed for three images which gives the performance criteria for DCT image compression technique. The rural image and urban image obtained by Indian Remote Sensing Satellite IRS 2 are used for deriving compression ratios. Lena image gives higher compression ratio compared to satellite rural and urban images. It is found that the rural image shows better compression ratio compared to urban image. It is seen that satellite rural image shows higher compression ratio of 7.8952 when compared to satellite urban image of 5.4244.
机译:图像压缩形成数字图像存储和传输的不可分割的一部分。存储和带宽容量的限制带来了图像压缩的必要性。离散余弦变换(DCT)是这里用于将空间组件转换为频率分量的技术。开发了一种算法来计算产生图像压缩的DCT。使用逆离散余弦变换(IDCT)来解压缩压缩图像以获得重建图像。压缩比(CR),均方误差(MSE)和峰值信号对噪声比(PSNR)进行了三个图像,其给出了DCT图像压缩技术的性能标准。印度遥感卫星IRS 2获得的农村形象和城市形象用于导出压缩比。与卫星农村和城市形象相比,Lena Image提供更高的压缩比。结果发现,与城市形象相比,农村形象显示出更好的压缩比。可以看出,与5.4244的卫星城市形象相比,卫星农村形象的压缩比为7.8952。

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