An algorithm of image processing for underwater range finding by active triangulation

In this paper, we present an algorithm for range image processing to reduce effects of underwater environments on the quality of range finding. This algorithm of image processing is based on the principle of the least-squares error method, which fits discrete image data to continuous piecewise curves. To simply the fitting of image data, the interval of each row and column is subdivided into several subintervals. Then a straight line is used to fit the image data within the subinterval. To merge two adjacent lines together, a weighting technique with a linear weighting factor is imposed. After the image is processed, it will provide a better imaging quality than the original one if values of the design parameters are properly assigned. Thus, a series of design of experiment process runs are carried out to study effects of the design parameters on quality of range finding. To make the proposed algorithm robust against noises, both environmental illumination and turbidity are forced into the experiments by utilizing an outer array. From the results of the range finding experiments, it was found that the proposed algorithm of image processing in truth has potential of increasing quality of range finding. The results also show that the proposed algorithm can achieve high quality of range finding only having the processing of row elements. Also, the quality of range finding by using the proposed algorithm of image processing is superior to that of using a bandpass optical filter.