The thesis addresses some known methods of underwater image processing with the goal of visualy improving images and creating a larger panoramic image.
The first aim of the thesis is to use known and promising methods for image enhancement and image restoration and apply them to underwater video sequences of the sea floor.
Image enhancement methods that were being tested were gamma correction, histogram equalization and adaptive histogram equalization.
Image restoration methods that were being tested were unsharp masking, blind deconvolution and wiener filtering.
The second aim of the thesis is to produce a panoramic image of a better quality than the individual images by geometric alignment of images in a time sequence and by combining overlapping images together.
The first step was to match neighboring frames by extracting features using a SIFT algorithm and then using those feature pairs, to estimate geometric transformation matrices, that we need for alignment of frames.
Tested methods for creating panoramic images were blending, median filtering and a method, that built a panoramic image by selecting pixels of those images, whose centers were closest to the location of that pixel.
The whole thesis was realized and tested in MATLAB.
We selected the most appropriate method of image enhancement and restoration by visually comparing images before and after processing.
Of all the tested methods of image enhancement and restoration, adaptive histogram equalization and unsharp masking were picked as the most appropriate one.
Of all the tested methods of panoramic image creation, the one that based on calculating distances was picked as the most appropriate one.