Sonar image processing for improved underwater environment modelling

The purpose of the study was to present a sequence of development of an algorithm for improving the quality of images obtained using side-scan sonar. Mathematical image processing techniques such as contrast enhancement, edge processing, and colorimetric techniques were used to achieve this goal. Steps to improve image contrast included normalising signal intensity, adaptive contrast enhancement using limited contrast alignment of histograms, and correction of uneven lighting. The sonar radiation pattern and image intensity normalisation scheme were demonstrated. The contrast limited adaptive histogram equalisation filter showed higher values of the peak signal-to-noise ratio and structural similarity index compared to conventional histogram alignment, indicating better preservation of detail, image structure, and noise reduction. Analysis of edge processing, in particular by Canny and Sobel, has shown their potential effectiveness in improving the detail of underwater structures. In addition, the use of Gaussian smoothing allowed reducing the level of high-frequency noise and make textures smoother. As a result, there was a decrease in graininess, softness of object contours, and overall smoothing of the scene. In addition, cubic spline regression showed normalised image data. In turn, colorimetric analysis focused on converting images between greyscale and colour spaces, which made it easier to identify underwater objects and structures. An example of Hue-Saturation-Value components was given, which demonstrated different effects on the quality of sonar image visualisation. The Value component provided the most expressive distinction between the object and the background, while the Hue component was ineffective for structure analysis. The combination of Value and Saturation allowed for improved contour detail. Optimisation of the pseudo-colour gamut allowed adapting the image to different tasks, contributing to more accurate object recognition. The results obtained confirm the feasibility of using the presented methods in a wide range of applied tasks related to visualisation and analysis of underwater environments