Discrete Wavelet Transform-Based Satellite Image Resolution Enhancement



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INTRODUCTION

RESOLUTION of an image has been always an important
issue in many image- and video-processing applications,
such as video resolution enhancement [1], feature extraction
[2], and satellite image resolution enhancement [3].
Interpolation in image processing is a method to increase
the number of pixels in a digital image. Interpolation has been
widely used in many image processing applications, such as
facial reconstruction [4], multiple description coding [5], and
image resolution enhancement [6]–[8]. The interpolation-based
image resolution enhancement has been used for a long time
and many interpolation techniques have been developed to
increase the quality of this task. There are three well-known
interpolation techniques, namely, nearest neighbor, bilinear,
and bicubic. Bicubic interpolation is more sophisticated than
the other two techniques and produces smoother edges.


WAVELET-BASED IMAGE RESOLUTION ENHANCEMENT

There are several methods which have been used for satellite
image resolution enhancement. In this paper, we have used two
state-of-art techniques for comparison purposes. The first one
is WZP and CS [17], and the second one is the previously
introduced CWT-based image resolution enhancement [3].


DWT-BASED RESOLUTION ENHANCEMENT

As it was mentioned before, resolution is an important feature
in satellite imaging, which makes the resolution enhancement
of such images to be of vital importance as increasing the
resolution of these images will directly affect the performance
of the system using these images as input. The main loss of an
image after being resolution enhanced by applying interpolation
is on its high-frequency components, which is due to the
smoothing caused by interpolation. Hence, in order to increase
the quality of the enhanced image, preserving the edges is
essential.


RESULTS AND DISCUSSIONS
The proposed technique has been tested on several different
satellite images. In order to show the superiority of the proposed
method over the conventional and state-of-art techniques from
visual point of view Figs. 8–10 are included. In those figures
with low-resolution satellite images, the enhanced images by
using bicubic interpolation, enhanced images by using WZPand
CS-based image resolution enhancement, and also the enhanced
images obtained by the proposed technique are shown.
It is clear that the resultant image, enhanced by using the
proposed technique, is sharper than the other techniques.