By Paul Klint
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For both the methods, I and Q components are linearly interpolated and Y component alone is zoomed by the appropriate methods. 14). We can readily observe the proposed performing better than spline interpolation method (it is not apparent in the monochrome versions of images, but, for color images, difference is apparent). Image quality may further be improved by pre and post-processing techniques. 1. K-L Transform The KL transform method is used for multi spectral images - color images, in our case.
According to Fig. 15. purposes). 16. 8b), visual qualities of spline and scaling function based methods are comparable, and seem to perform better. However, both of them smooth out some sharp edges of original low-resolution images. This can be observed at the rope which is tied to the tyre in boat image (Fig. 7b). We evaluate the performance of different techniques by calculating Peak Signal to Noise Ratio (PSNR), which is defined as: where, X is the original image and is the zoomed image. 1) Note: To calculate PSNR, a low resolution version of the high resolution image is zoomed.
DAUB4 wavelet was used for computing the discrete wavelet transform. Pseudocode for the above scheme is: BEGIN take two level wavelet transform of image(x) size M x M ; /* for box II of Fig. 2(a) */ FOR i=M/2 TO M DO FOR j = 0 TO M/2 DO find the max coefficient in box II ; T= max/2 ; FOR i=M/2 TO M DO FOR j = 0 TO M/2 DO BEGIN IF (x[i][j] && x[i/2][j/2] > T ) estimate wavelet coefficients for box II END FOR /* Repeat for boxes V and VII **/ take 3-level inverse wavelet transform of x to get 2M x 2M image ; END.
A Study in String Processing Languages by Paul Klint