Threshold estimation by adapting standard deviation at wavelet details subbands for image compression
In this paper, a new algorithm using wavelet properties to compress an image is proposed. This algorithm concern on reducing the wavelet coefficients produced by the Discrete Wavelet Transform (DWT) process. The proposed algorithm start with calculating the threshold value by using the proposed thre...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Published: |
Asian Research Publishing Network
2015
|
| Subjects: | |
| Online Access: | http://www.arpnjournals.com/jeas/index.htm http://www.arpnjournals.com/jeas/index.htm http://eprints.uthm.edu.my/7379/1/ARPN_shahidah.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | In this paper, a new algorithm using wavelet properties to compress an image is proposed. This algorithm concern on reducing the wavelet coefficients produced by the Discrete Wavelet Transform (DWT) process. The proposed algorithm start with calculating the threshold value by using the proposed threshold value estimator at wavelet detail subbands (Diagonal, Vertical and Horizontal subband). This proposed algorithm will estimate the suitable threshold value for each individual subband. The calculated threshold values are then applied to its’ respective subband. The coefficient with a lower value than the calculated threshold will be discarded while the rest are retained. The novelty of the proposed method is it use the principle of the standard deviation method of deriving the threshold value estimator equation. Experiments show that the proposed method can effectively remove a large amount of unnecessary wavelet coefficient with a higher Peak Signal to Noise Ratio (PSNR) and compression ratio as well as shorter elapse time. |
|---|