Curvelet Transform and Its Application in the Analysis of Pulp Fibre Images

The curvelet transform has received more and more attention in recent years due to its unique characteristics. This new mathematic transform is based on the Fourier transform, wavelet transform and Radon transform. It has overcome some limitations of wavelet in representing orientations of edges in image. The theory and implementation of curvelet transform is summarized. Its representative applications are introduced in view of their corresponding characteristics compared with other prevailing techniques. Finally, we introduced the curvelet transform in the analysis of paper pulp fibre images. In order to detect the morphologic parameter of the pulp fibres, first we need to disjoin the intersect fibres. The image processing algorithm is proposed to extract the characteristics of the collected fibre, which can be done after image denoising, enhancement and edge detection. We use the curvelet transform to analyze the pulp fibre image. Then extract the different characteristics of each fibre, to disjoin the intersect fibres. Experiment results show that the proposed techniques obtained perfect effects in the analysis of pulp fibre images