We consider in this paper the problem of image inpainting in infrared image analysis, where the objective is to reconstruct missing or deteriorated parts of an image. In this work, we develop image inpainting using quaternion representation concepts and modified exemplar-based technique. In our work, we exploit the concept of sparse representation, which takes a group of nonlocal patches with similar textures as the basic unit instead of a patch. As a result, the proposed method provides plausible restoration while propagating information of edge for the target region. Experimental inpainting results demonstrate the effectiveness of the proposed method in the task of reconstruction thermal images.
The fusion of data obtained in different electromagnetic ranges is an important task for many areas of research. The combining data is necessary for security systems (when searching for people in difficult weather conditions (snow, fog, rain, dust), automated control systems (auto-driving, UAVs), etc. The process of data analysis involves identifying base features. It includes the search and selection of borders, salience maps (human attention cards), angles, analysis of color gradients, etc. Most often, the detected features highlighted in images recorded in one range do not coincide with data obtained in other ranges. This is due to the fact that different electromagnetic ranges operate with different physical characteristics of objects in frames. The paper presents an approach based on the search and analysis of the basic descriptive characteristics of objects and the search for their correspondences on images of the same object, recorded in different electromagnetic ranges. As such data, the directions of the gradients are revealed, the search for the boundaries and angles of objects, the selection of locally stationary regions, the search for the center of mass of objects, the identification of the middle lines of stationary regions with included structures. The search for features is carried out on the basis of data obtained at various scales. Simplification of images is carried out on the basis of an algorithm for analyzing stationary regions and replacing the current intensity with an average. On the set of test data obtained in the visible range, near and far-infrared range, depth maps, the applicability of the proposed approach is shown. As an example of the applicability of this approach, an example is shown of stitching a pair of images obtained in different electromagnetic ranges.