Proceedings Article | 15 November 2007
KEYWORDS: Image restoration, Edge detection, Image processing, Wavelets, Wavelet transforms, Image filtering, Image segmentation, Process modeling, Digital signal processing, Point spread functions
We present an effective image recovering method .Edge information are very important, we can detect the edge of
the image via wavelet transform before recovering the image. In this paper, we give a simple and effective method to
detect the edge information. The first, we can decompose the image using a wavelet transform, the high frequency
information is corresponding to the edge and noise, the edge and noise have different properties, as follows: the
orientation of edge is very strong, but the noise is non-orientation. On base of that, we can decompose the edge and noise
in horizontal orientation, vertical orientation, and diagonal orientation. Because the edge is directional, its values in each
orientation have much difference; in opposition, noise is non-orientation, its values are almost same. We can set the
threshold based on the variances of difference in each orientation. By this time, we gain the edge without noise. For the
rest, we can restore using regularization. Now the low frequency is corresponding to the flat. In this paper, we detect the
edge by the wavelet, so can choose a bigger parameter to recover. At last, we add the edge and the part of regularized
image restoration. This method has advantage in holding the edge and is simple to choose the parameter of regularization.
Experimental results show the good performance, this method can keep image's of edge from degradation and increase
PSNR up to 1~2dB.
