3D Improve Zero Memory Set Partitioned Embedded BloCK Coding Algorithm for Hyperspectral Image

Abstract

Hyperspectral imaging maintain a crucial role for the remote sensing technologies. But, the amount of image data produce by the image sensors is huge, thus handling of this image data become an issue with the sensor and it’s performance. A compression algorithm is required to save the sensor memory, reduce data complexity and improves sensor performance. In past, many compression algorithms had been proposed but transform based compression algorithms performed better than other type of compression algorithms such as embeddedness, high coding efficiency and low coding complexity. Wavelet transform based compression algorithm has low coding memory and 3D Zero Memory Set Partitioned Embedded bloCK (3D-ZM-SPECK) achieve zero coding memory but has slightly low coding efficiency. To obtain higher coding efficiency, present compression algorithm is an advance version of 3D-ZM-SPECK which exploits spectral redundancy to achieve the high coding efficiency. It has been noticed from the simulation results on two different images that present compression algorithm high coding efficiency (∼4% to 5%) and zero coding memory requirement.