3D Openjpeg2000 With Integer KLT - Mamat, Shahrul Azmam (Universiti Sains Malaysia, 2018)
A hyperspectral image processing system especially remote sensing technology is very important as it able to provide extremely useful information for the various type of Earth monitoring system – terrains, weather, oceanology, pollution control and etc. Hyperspectral image which includes the spatial (inter-pixel) and spectral (multi-component images) redundancy. The amount of acquired data of the hyperspectral image greatly increased since the spectral and spatial resolution of sensors which monitoring Earth terrains increase as well. Increased size of imagery data will require an image compression as there are lot issues need to overcome, such as downlink speed for bandwidth image and on-board satellite database storage are limited. The distance and downlink speed for image transmission from Earth Observation (EO) Satellites to the ground station need to be measured. The developed image processing system need to optimize the compression performance of image data in order to maximize the transmission of image data as well as high speed downloading capacity. The compression and decompression algorithm include in Integer Karhunen-Loève Theorem (Integer KLT) which efficient in spectral decorrelation and OpenJPEG2000 is a suitable for spatial decorrelation. The lossless compression ratio (CR) and execution time (ET) of hyperspectral image in *.rawl file from OpenJPEG2000 will be compared to get better result which will lead the improvement of EO Technology for reduction of data size which allows more images to be stored in the on-board satellite database storage and also shorter the time required to transfer the images from EO satellites to the ground station within a single pass.