Table of Contents

1 Introduction and overview.- 2 Linear scale-space and related multi-scale representations.- 3 Scale-space for 1-D discrete signals.- 4 Scale-space for N-D discrete signals.- 5 Discrete derivative approximations with scale-space properties.- 6 Feature detection in scale-space.- 7 The scale-space primal sketch.- 8 Behaviour of image structures in scale-space: Deep structure.- 9 Algorithm for computing the scale-space primal sketch.- 10 Detecting salient blob-like image structures and their scales.- 11 Guiding early visual processing with qualitative scale and region information.- 12 Summary and discussion.- 13 Scale selection for differential operators.- 14 Direct computation of shape cues by scale-space operations.- 15 Non-uniform smoothing.- A Technical details.- A.1 Implementing scale-space smoothing.- A.2 Polynomials satisfying the diffusion equation.

Reviews

` This approach will certainly turn out to be part of the foundations of the theory and practice of machine vision ... the author has no doubt performed an excellent service to many in the field of both artificial and biological vision. '
Jan Koenderink