**5. Conclusion**

In this Chapter first a novel statistical encoding algorithm was presented. The proposed SE algorithm assumes that the distribution of the coefficients in the input matrix is partly Gaussian and uses a hierarchal encoding algorithm to estimate the coefficients in the input matrix with the Gaussian mean values of multiple distributions; then a multi-resolution and statistical based image-coding scheme was developed. It applies a 2D wavelet transform on the input image data to decompose it into its frequency subbands. The baseband is losslessly coded to preserve the visually important image data. The coefficients in each detail subband were first dc level shifted to have a minimum value of zero and then coded using the SE algorithm. The SE algorithm takes the dc level shifted coefficients of a detail subband and a threshold value, which is generated for that subband. The encoding process is then performed. Perceptual weights were calculated for the centre of each detail subband and used to regulate the threshold value for that subband.

Experimental results showed that the proposed coding scheme provides significantly higher subjective and objective quality when perceptual weights are used to regulate the threshold values. The results also indicated that the proposed codec outperforms JPEG and JPEG2000 coding schemes subjectively and objectively at low compression ratios. Results showed that the proposed coding scheme outperforms JPEG subjectively at higher compression ratios. It offers comparable visual quality to that of JPEG2000 at high compression ratios.

Wavelet Based Image Compression Techniques 443

a) MSB with HVS b) MSB without HVS

Fig. 10. Reconstructed I) 'Lena', II) 'Elaine' and II) 'House' test images at compression ratio

of 16 using the MSB codec a) with HVS and b) without HVS.

I) Lena

II) Elaine

III) House

Fig. 9. PSNR measurements for a) 'Lena', b) 'Elaine' and c) 'House' test images at different compression ratios using MSB codec with and without employing perceptual weights.

Fig. 9. PSNR measurements for a) 'Lena', b) 'Elaine' and c) 'House' test images at different compression ratios using MSB codec with and without employing perceptual weights.

a) Lena

b) Elaine

c) House

a) MSB with HVS b) MSB without HVS

Fig. 10. Reconstructed I) 'Lena', II) 'Elaine' and II) 'House' test images at compression ratio of 16 using the MSB codec a) with HVS and b) without HVS.

Wavelet Based Image Compression Techniques 445

a) Lena b) Elaine

Fig. 12. Reconstructed a) 'Lena' and b) 'Elaine' test images at compression ratio of 5 using

I) MSB

II) JPEG

III) JPEG 2000

I) MSB codec, II) JPEG and III) JPEG2000.

Fig. 11. PSNR measurements for a) 'Lena', b) 'Elaine' and c) 'House' test images at different compression ratios using MSB, JPEG and JPEG2000 codecs.

Fig. 11. PSNR measurements for a) 'Lena', b) 'Elaine' and c) 'House' test images at different

compression ratios using MSB, JPEG and JPEG2000 codecs.

a) Lena

b) Elaine

c) House

Fig. 12. Reconstructed a) 'Lena' and b) 'Elaine' test images at compression ratio of 5 using I) MSB codec, II) JPEG and III) JPEG2000.

Wavelet Based Image Compression Techniques 447

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Fig. 13. Reconstructed a) 'Lena' and b) 'Elaine' test images at compression ratio of 40 using I) MSB codec, II) JPEG and III) JPEG2000.
