Zero-padding in DWT satellite image compression

• Main Authors: Shafie, Suhaidi, Al-Obaidi, Halah Saadoon Shihab, Ahmad, Fauzan, Ramli, Abdul Rahman
• Format: Article
• Language: English
• Published: Universiti Putra Malaysia Press 2017
• Online Access: http://psasir.upm.edu.my/id/eprint/55867/1/24-JTS%28S%29-0138-2016-4thProof.pdf; http://psasir.upm.edu.my/id/eprint/55867/; http://www.pertanika.upm.edu.my/Pertanika%20PAPERS/JST%20Vol.%2025%20(S)%20Feb.%202017/24-JTS(S)-0138-2016-4thProof.pdf

Discrete Wavelet Transform (DWT)-based image compression techniques have been utilized in most of the earth observation (EO) satellites launched during the last few decades, since they have proved to be more efficient than other methods used previously with remote sensing multispectral imaging payloads. The efficiency of these techniques is mainly due to their high compression ratio that can be achieved while maintaining the quality of the compressed image. Also, they are considered multi-resolution compression techniques. However, these techniques are considered computationally demanding, due to their complex and sophisticated hardware. Due to the limited computational resources available on-board small satellites, they are considered one of the important criteria when choosing the satellite image compression method, along with the compression ratio and quality of the reconstructed image. Hence, an alternative DWT-based method was proposed, developed and implemented in this work with the aim of reducing the computational resources on-board a small satellite, replacing the regular DWT thresholding and quantization processes that are usually used to achieve lossy compression, with the zero-padding technique. This method will also help to control the change in the compression ratio and quality of the reconstructed image according to the end-user's scientific needs of the satellite image. The results of this work indicated, objectively and subjectively, that a decrease in the computational resources required on-board satellites was achieved by decreasing the processing time needed to complete the compression, without a significant difference in quality of the image reconstructed at the ground station.