Satellite Image Compression Using DCT Technique

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.