| dc.description.abstract | The enhancement of digital images is necessary in many fields of application of images. It makes it easier
for human viewers and machines to extract, interpret, and where necessary perform further processing
on the information contained in the images.
In this thesis, a spatial-spectral enhancement solution is proposed for degraded images captured using a
cell phone camera. The degradations addressed here are those caused by factors such as poor
resolution, fading, noise, shadows, poor illumination, geometrical distortions and ink smears which may
lead to erroneous interpretation of the image information.
A Nokia model 1680 cell phone camera was used to capture the images which were then loaded to a
computer using the Nokia PC suite software version 7.1 and converted to 8-bit grey-scale images using
MATLAB version 7.14. The grey scale images were then interpolated using a bicubic method to a size of
480x640 pixels. The interpolated images were enhanced by contrast stretching followed by single-scale
retinex enhancement. Optimal global thresholding was then used to binarise the images and finally,
morphological dilation was performed to yield enhanced images. For geometrically distorted document
images, an additional procedure based on 2-D processing was carried out on the morphologically dilated
images to rectify the distortions.
Computer simulation based experiments have been used to demonstrate the effectiveness of the
proposed algorithm. The results show a significant improvement over those obtained using other
proposed methods in terms quality measures and performance of optical character recognition
applications. | en |
