Satellite image compression using integer wavelet regression
Md. Al Mamun, Md. Ali Hossain, Md. Nazrul Islam Mondal, Mumu Aktar · 2017
Multi-temporal Image Compression is now an immerging field considering the fact that terabytes of data is now available for download every day. Evantualy temporal data compression is becoming a critical issue for fast data transmission. Many works have been done regarding compression in the field of satellite images that utilizes the spectral and spatial redundancies using predictive and transformed based procedures for lossless data compression, but, most of the contributions are on individual data or on single data. The main objective of this paper is to exploit the temporal correlation between the images. The recent image will be predicted from the historical image that is already available to the user. This will substantially reduce the load in transmitting the images. This paper actually emphasis on the process of increasing temporal correlation, which consequently improves the compression gain. In sequential transmission, the transmitted data will be used in future as a reference. Therefore, a new lossless approach has been introduced where reversible integer wavelet transformation is used to improve the temporal correlation. The experimented results show that the proposed method outperformed many state of art lossless approaches including JPEG2000.