IMAGE COMPRESSION ON SCANNING TECHNIQUES: Experimental Results

White noise is added to the original image.

Discrete Wavelet Transform method is used in the noisy image.
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Fig6Image Compression On_decrypted Fig7Image Compression On_decrypted
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To apply the Row order scan method.
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To apply the Morton order scan method.
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Karhunen – Loeve Transform is applied in the Row order and Morton order for compression.
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Active pixel size is calculated Row order technique and Morton techniques are compared.
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Technique CR MSE PSNR
DWT+Row order 7.79258 0.300956 10.4300
DWT+Morton 7.84647 0.298889 10.4898

CONCLUSION

In this paper, the wavelet based data thinning methodologies have been developed and tested. The wavelet of the satellite data result in the noise free field giving greater information about the closeness of the true fields and also this type of transform results in progressive transformation of the data when compare to other transform. The compression obtained by Karhunen-Loeve Transform resulted in the better compression ratios with Row order and Morton order scanning methods. The combined version of the Discrete Wavelet Transform and Karhunen-Loeve Transform applied to an image yield a better image quality and the compression rate which were evaluated with the minimized Mean Squared Error and higher Peak Signal to Noise Ratio in addition the Morton order Scan resulted in a better compression ratio when compared to Row order scan due to the extraction of the pixels can be done one after another within a block which cannot be obtained in the Row order due to the serial transmission.