Pyramid transform and scale-space analysis in image analysis

Abstract

The pyramid transform compresses images while preserving global features such as edges and segments. The pyramid transform is efficiently used in optical flow computation starting from planar images captured by pinhole camera systems, since the propagation of features from coarse sampling to fine sampling allows the computation of both large displacements in low-resolution images sampled by a coarse grid and small displacements in high-resolution images sampled by a fine grid. The image pyramid transform involves the resizing of an image by downsampling after convolution with the Gaussian kernel. Since the convolution with the Gaussian kernel for smoothing is derived as the solution of a linear diffusion equation, the pyramid transform is performed by applying a downsampling operation to the solution of the linear diffusion equation. © 2012 Springer-Verlag.