Two large-exposure-ratio image fusion by improved morphological segmentation.

Abstract

The fusion of two large-exposure-ratio images, especially in the rocket launch field, is a challenging task because of fast-moving objects and differential features from daily scenes. Based on the large-exposure-ratio images, we propose a principle of halo formation at the boundaries of over-exposed areas. To avoid the halos in the fusion images, an improved morphological segmentation (IMS) method is developed to segment the over-exposed regions and boundaries. The IMS method is inspired by the mountain topography and builds a bridge between the 3D patches and quadratic polynomial coefficients. An improved multiscale method with segmentation in high-exposed images is proposed. In the rocket launch observation experiment, we constructed a two-camera simultaneous imaging system to avoid the dynamic scenes. The result of our proposed fusion method could best preserve the details and colors of the flames in low-exposed images and has the best subjective observation. The objective matrices also demonstrate superior edge and contrast performances over mainstream methods.