The relentless growth in digital image data and its widespread application across various fields such as medical imaging, satellite imaging, and online content delivery necessitates efficient compression techniques to reduce storage requirements and facilitate faster transmission. However, traditional compression methods often lead to a significant degradation in image quality, particularly at high compression ratios, making the recovery of the original image fidelity challenging. This paper investigates the impact of compression ratio and PSNR on image quality, utilizing the 256×256 as a test image. It introduces a novel technique combining discrete wavelet transforms with Db2 wavelet and various de-noising filters (Wiener, Median) to enhance decompression quality measures, such as SNR and BER, over existing methods. Further exploration is conducted on the effect of increasing compression ratios on image quality in flat fading channels using QPSK and 8-PSK modulation techniques with the Db2 wavelet transform. Comparative results demonstrate the efficacy of the proposed technique in maintaining higher quality in decompressed images. This study not only underscores the trade-off between compression ratio and image quality but also showcases the potential of Db2 wavelet transforms in improving performance in fading channel conditions for different modulation schemes.
Image Compression, Discrete Wavelet Transform, Db2 Wavelet, De-noising Filters, SNR and BER, Flat Fading Channels, QPSK and 8-PSK Modulations
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