DCT and DWT based image compression in remote sensing images

With the improvement of synthetic aperture radar technology, larger areas are being imaged and the resolution of the images has increased. Larger images have to be transmitted and stored. Due to the limited storage and downlink capacity on the airplane or satellite, the volume of data must be reduced. This makes compression of SAR images with minimal loss of information important. This study aims to compare the best-known compression techniques, namely discrete cosine transform and discrete wavelet transform. It investigates RADARSAT and SPOT images of different regions of different characteristics. The regions investigated are sea areas, forest areas, and residential and industrial areas which define different patterns of urban land use. The studies showed that compression ratios changed according to the pixel classification. The second purpose of this study is to compare the two compression algorithms. The DWT based algorithm gave the minimum mean square error compared to the DCT based compression algorithm. The results changed according to the quantization process and the transform-coding algorithm.