Developed a Method for Satellite Image Compression Using Enhanced Fixed Prediction Scheme

Image is widely used in modern life which produces huge amounts of data and that required to store them with minimized space. Image compression is the mechanism by which a digital image is effectively compressed to minimize the number of bits used to display an image. The images take huge space in the computers or servers, hence a long time during transmission. This paper provides an enhanced compression method to reduce the store size and the cost of transmission using a fixed predictive scheme. Predictive coding eliminates spatial redundancy between successive neighboring pixels since only a few information outcomes have to be encoded. This paper suggested an enhanced method to improve image compression of Satellite Images without missing data by using a static structure (predictions) that compresses image data without loss based on the fixed prediction technique. The Satellite Images data was used to test the enhanced method by using six Satellite Images. The achieved results were very promising conducting a compression ratio up to 79.35%. The SNR/PSNR was tested to check the quality of the compressed images with a value =38.30.