Gray Image Coding Based on Contourlet Transformations: Image Coding - Teba M. Ghaze Al-Solaivany
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Toimitus 15-21 arkipäivässä
30 päivän palautusoikeus
Most of the applications on EZT algorithm were applied on wavelet transformation. In the last ten years, the contourlet transformation has shown its higher efficiency compared to the wavelet transformation as it is able to deal with multidirections instead of the vertical and horizontal directions covered by the wavelet transformation.In the present research, the contourlet coefficient has been adopted as a ... Täydellinen kuvaus
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Loppu
Kuvaus
Most of the applications on EZT algorithm were applied on wavelet transformation. In the last ten years, the contourlet transformation has shown its higher efficiency compared to the wavelet transformation as it is able to deal with multidirections instead of the vertical and horizontal directions covered by the wavelet transformation.In the present research, the contourlet coefficient has been adopted as an input to the EZT (which are normally a wavelet coefficient). Arranging the contourlet coefficient to be studied as an input to EZT, the result of adopting modified contourlet coefficient has been studied on two parameters, namely the file size and threshold value, and also been tested by evaluating three factors, viz. correlation, MSE and PSNR.Studying the effect of the contourlet coefficient to see which of them have the high effects and the effect of the levels of composition. The result shows that the high components of the coefficient have low effect with high compression ratio in addition to high correlation factor.
Lisätietoja
| Kirjoittaja | Teba M. Ghaze Al-Solaivany |
|---|---|
| Julkaisija | Noor Publishing |
| Julkaisuvuosi | 2020 |
| Kannen tyyppi | Pehmeäkantinen |
| EAN | 9786202788977 |