Medical image fusion is widely used in various clinical procedures for the precise diagnosis of a disease. Image fusion procedures are used to assist real‐time image‐guided surgery. These procedures demand more accuracy and less computational complexity in modern diagnostics. Through the present work, we proposed a novel image fusion method based on stationary wavelet transform (SWT) and texture energy measures (TEMs) to address poor contrast and high‐computational complexity issues of fusion outcomes. SWT extracts approximate and detail information of source images. TEMs have the capability to capture various features of the image. These are considered for fusion of approximate information. In addition, the morphological operations are used to refine the fusion process. Datasets consisting of images of seven patients suffering from neurological disorders are used in this study. Quantitative comparison of fusion results with visual information fidelity‐based image fusion quality metric, ratio of spatial frequency error, edge information‐based image fusion quality metric, and structural similarity index‐based image fusion quality metrics proved the superiority. Also, the proposed method is superior in terms of average execution time to state‐of‐the‐art image fusion methods. The proposed work can be extended for fusion of other imaging modalities like fusion of functional image with an anatomical image. Suitability of the fused images by the proposed method for image analysis tasks needs to be studied.
Earth consists of hard rock layers where water is restricted to secondary permeability, and thus to fractures and the weather zones. Structural geology studies, geologic lineaments and their pattern information are essential for better planning and execution of projects to avoid any natural hazards. Satellite images, aerial photographs and digital elevation models will give lineament information. Recent advances in digital image processing allow such lineament extraction to be accomplished in semi-automatic to fully automatic approaches. The accuracy of extracting lineaments depends strongly on the spatial resolution of the imagery, higher resolution imagery result in a higher quality of lineament map. In this paper, an attempt has been made for Mapping of lineaments and knowledge base preparation using geomatics techniques for part of the Godavari and Tapi Basins, India. A methodology for lineament extraction and the design of a knowledge-based lineament identification system has been proposed for geological aspects of any developmental activity. This methodology might potentially be adopted for the identification of several features of geological or anthropogenic origin. The study results of lineaments and the rose diagrams of the extracted lineaments can be applied to structural geology studies and their applications such as oreforming systems, mineral exploration, petroleum, nuclear energy facility sittings and water resource investigations, groundwater studies and also for finding suitable sites for dams and reservoirs.
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