An Enhanced Approach for Low Bit Rate Image Compression Using Autoregressive Modeling
IOSR Journal of VLSI and Signal processing · 2013
In this paper, we are going to use a practical approach of uniform down sampling in image space and yet making the sampling adaptive by spatially varying, directional low-pass pre-filtering.The resulting down-sampled pre-filtered image remains a conventional square sample grid, and, thus, it can be compressed, transmitted without any change to current image coding standards and systems.The decoder first decompresses the low-resolution image and then up-converts it to the original resolution in a constrained least squares restoration process, using a 2-D piecewise autoregressive model and the knowledge of directional low-pass prefiltering.The proposed compression approach of collaborative outperforms JPEG 2000 in PSNR measure at low to medium bit rates and achieves superior visual quality, as well.The superior low bit-rate performance of the Collaborative Adaptive Down-sampling and Upconversion (CADU) approach seems to suggest that oversampling not only wastes hardware resources and energy, and it could be counterproductive to image quality given a tight bit budget.