Robust Feature Matching Using Haze Removal Based on Transmission Map for Aerial Images

Single Image Haze Removal with Pixel-based Transmission Map Estimation

Adversary imaging condition such as in a hazy weather is a challenge in the community of image processing. To address the challenge of haze removal, several model-based approaches have been reported recently. Among them, a single image haze removal scheme based on dark channel prior (DCP) was presented in [1] and has been getting popular because of its satisfactory performance for most of cases...

Feature extraction from aerial images and structural stereo matching

In this paper, a method of generating structural descriptions of stereo image pairs and their matching to recover 3-D form of objects in space, is discussed. The method consists of the following steps: rstly, straight line segments are extracted in both images and the relations among them are investigated. The relational subgraphs are constructed then, and the correspondence graph is created. U...

Robust Matching of Aerial Images with Low Overlap

This paper addresses the problem of aerial image matching. We analyze existing approaches to this problem and show that, though the modern algorithms cope with the task quite well, their results are deteriorated in case of low overlap and significant rotation angle between the images. A two-stage feature-based image matching scheme is presented. It is shown that preliminary stage of simplified ...

Feature-based Georegistration of Aerial Images

Robust Feature Extraction and Matching for Omnidirectional Images

This paper presents a new and robust method for extracting and matching visual vertical features between images taken by an omnidirectional camera. Matching robustness is achieved by creating a descriptor which is unique and distinctive for each feature. Furthermore, the proposed descriptor is invariant to rotation. The robustness of the approach is validated through real experiments with a whe...