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Low Bit-Rate Image Compression using Adaptive Down-Sampling technique

Author(s): V.Swathi | Prof K.Ashok Babu

Journal: International Journal of Computer Technology and Applications
ISSN 2229-6093

Volume: 02;
Issue: 05;
Start page: 1679;
Date: 2011;
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Keywords: Autoregressive modeling | compression standards | image restoration | image upconversion | low bit-rate image compression | sampling | subjective image quality

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 and 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 pre-filtering. The proposed compression approach of collaborative adaptive down-sampling and up-conversion (CADU) 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 CADU approach seems to suggest that over-sampling not only wastes hardware resources and energy, and it could be counterproductive to image quality given a tight bit budget.
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