ion levels for image fusion The fusion of an image series can take place on different abstraction levels (Fig. 1): • Within a data-level fusion (pixel-level fusion), the combination takes place at the level of the image data, i.e. the gray or RGB values. The precondition of a data fusion is that the images have been recorded with homogeneous sensors.

Until now, of highest relevance for remote sensing data processing and analysis have been techniques for pixel level image fusion. So, This paper attempts to undertake the study of Feature-Level based image fusion. For this purpose, feature based fusion techniques, which are usually based on empirical or heuristic rules, are employed. Hence, in this paper we consider feature extraction (FE) for...

Image fusion software can derive a fusion image from single photon emission computed tomography and computed tomography scans. We applied a three-dimensional fusion image to detect sentinel lymph nodes (SLNs) in 3 patients with malignant melanomas of the lumbar, vulvar and head region, respectively. During each operation, we detected SLNs at the expected site, as indicated by the fusion images....

Medical image fusion has been used to derive useful information from multimodality medical image data. In this research, we propose a novel method for multimodality medical image fusion. Using wavelet transform, we achieved a fusion scheme. Afusion rule is proposed and used for calculating the wavelet transformation modulus maxima of input images at different bandwidths and levels. To evaluate ...

In this paper, we present a gradient domain image fusion framework based on the Markov Random Field (MRF) fusion model. In this framework, the salient structures of the input images are fused in the gradient domain, then the final fused image is reconstructed by solving a Poisson equation which forces the gradients of the fused image to be close to the fused gradients. To fuse the structures in...

1.1 Definition of image fusion With the development of multiple types of biosensors, chemical sensors, and remote sensors on board satellites, more and more data have become available for scientific researches. As the volume of data grows, so does the need to combine data gathered from different sources to extract the most useful information. Different terms such as data interpretation, combine...

Image fusion has wide range of application in satellite images, general photography, medical images etc. Image fusion is the process in which we combine two or more images or some features of images to form a single image which is free from distortion and does not loses its information. Images which are taken from different angles sometimes needs to be fused together to form a single image whic...

In this paper, a study on multi-focus image fusion methods having the ability to conquer the problems in transform domain method and to avoid the disabilities occurring in spatial domain method has been introduced. To gain an image with high quality and with all spectral and spatial information, it is important to recover the images from various multi-sensor images. Image fusions are mainly cla...

The traditional image fusion algorithm completed the fusion based on all pixel information. The time and space requirements are higher. The improved fusion algorithm used the theory of compressed sensing (CS) for the processing of remote sensing image fusion. Firstly, the source images using wavelet transform for sparse representation, then, the improved fusion algorithm used the observation ma...