Image Compression Based on Multilevel Adaptive Thresholding using Meta-Data Heuristics

Gowri Sankar Reddy D, Veera V.C. Reddy, (doi: 10.23953/cloud.ijarsg.29)


Satellite image processing involves very often the need of compression. The compression of satellite images will reduce storage requirements and conserves transmission bandwidth. In this paper, a lossy image compression method is proposed based on multilevel adaptive thresholding using Meta-Data heuristics to compress the Landsat-8 satellite images. In the proposed method the number of thresholds is fixed in accordance with the bitrate required and the Peak Signal to Noise Ratio (PSNR) is improved by entropy based adaptive thresholding. Test image of Landsat-8, Band 3, 5 is used for performing the compression and the performance metric PSNR is measured for uniform thresholding and the proposed method. The proposed method gives improvement in the PSNR and the method is computationally simulated using Fixed Point Binary scaling.


PSNR; BPP; DN (digital numbers); Threshold

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