COMPARISON OF SUB-SAMPLING ALGORITHM FOR LRIT IMAGE GENERATION

The COMS provides the LRIT/HRIT services to users. The COMS LRIT/HRIT broadcast service should satisfy the 15 minutes timeliness requirement. The requirement is important and critical enough to impact overall performance of the LHGS. HRIT image data is acquired from INRSM output receiving but LRIT image data is generated by sub-sampling HRIT image data in the LHGS. Specially, since LRIT is acquired from sub-sampled HRIT image data, LRIT processing spent more time. Besides, some of data loss for LRIT occurs since LRIT is compressed by lossy JPEG. Therefore, algorithm with the fastest processing speed and simplicity to be implemented should be selected to satisfy the requirement. Investigated sub-sampling algorithm for the LHGS were nearest neighbour algorithm, bilinear algorithm and bicubic algorithm. Nearest neighbour algorithm is selected for COMS LHGS considering the speed, simplicity and anti-aliasing corresponding to the guideline of user (KMA: Korea Meteorological Administration) to maintain the most cloud itself information in a view of meteorology. But the nearest neighbour algorithm is known as the worst performance. Therefore, it is studied in this paper that the selection of nearest neighbour algorithm for the LHGS is reasonable. First of all, characteristic of 3 sub-sampling algorithms is studied and compared. Then, several sub-sampling algorithm were applied to MTSAT-1R image data corresponding to COMS HRIT. Also, resized image was acquired from sub-sampled image with the identical sub-sampling algorithms applied to sub-sampling from HRIT to LRIT. And the difference between original image and resized image is compared. Besides, PSNR and MSE are calculated for each algorithm. This paper shows that it is appropriate to select nearest neighbour algorithm for COMS LHGS since sub-sampled image by nearest neighbour algorithm is little difference with that of other algorithms in quality performance from PSNR.