Contourlet Transform

The contourlet transform is a multiresolution image analysis technique designed to efficiently represent images containing directional information, particularly edges and contours. Current research focuses on leveraging its strengths in diverse applications, including image retrieval, medical image segmentation, and depth estimation in 360° imagery, often integrating it with neural networks to create hybrid models like "ContourletNets." These advancements demonstrate the contourlet transform's utility in improving image processing tasks by providing a more effective and interpretable representation than traditional methods, leading to enhanced performance in various computer vision applications.