image compression jpeg Highly Efficient Compression of Correlated Images with Rotation in a Distributed Environment Docket: UAH-P-08013 Technology UAH researchers have developed a highly efficient approach to compress geometrically transformed images in a distributed environment, with compression efficiencies an order-of-magnitude higher than those achieved by using the state-of-the-art techniques, such as JPEG and H.264. The Peak Signal to Noise Ratio (PSNR) is improved as well. This approach, called the Random Projection Approach treats the fundamental problem of inter-image correlation exploitation by using the Dimensionality Reduction methodology. The table below shows a comparison between the compression efficiencies of the three methods: Method JPEG H.264 RP PSNR (dB) 39.2 39.3 44.5 Compression Ratio 4.5:1 7.3:1 81.9:1 Applications Image compression Advantages Compression ratios can be an order-of-magnitude higher than those attained by JPEG and H.264 techniques Improves the peak signal-to-noise ratio An extremely low-complexity encoder can be used when this approach is incorporated in distributed source coding Status State of Development: Prototype Licensing Status: Available for licensing Patent Status: Proprietary