RIFT: Multi-Modal Image Matching Based on Radiation-Variation Insensitive Feature Transform

Traditional feature matching methods, such as scale-invariant feature transform (SIFT), usually use image intensity or gradient information to detect and describe feature points; however, both intensity and gradient are sensitive to nonlinear radiation distortions (NRD). To solve this problem, this paper proposes a novel feature matching algorithm that is robust to large NRD. The proposed method is called radiation-variation insensitive feature transform (RIFT). There are three main contributions in RIFT. First, RIFT uses phase congruency (PC) instead of image intensity for feature point detection. RIFT considers both the number and repeatability of feature points and detects both corner points and edge points…

• NN
  National Natural Science Foundation of China

  Award: 41901398
• CP
  China Postdoctoral Science Foundation

  Award: 2018M640734
• NS
  Natural Science Foundation of Hubei Province

  Award: 2019CFB167