On-board satellite image compression using the Fourier transform and Huffman coding

The need to transmit or store satellite images is growing rapidly with the development of modern communications and new imaging systems. The goal of compression is to facilitate the storage and transmission of large images on the ground with high compression ratios and minimum distortion. In this work, we present a new coding scheme for satellite images. At first, the image will be downloaded followed by a fast Fourier transform FFT. The result obtained after FFT processing undergoes a scalar quantization (SQ). The results obtained after the quantization phase are encoded using entropy encoding. This approach has been tested on satellite image and Lena picture. After decompression, the images were reconstructed faithfully and memory space required for storage has been reduced by more than 80%.