Combine Target Extraction and Enhancement Methods to Fuse Infrared and LLL Images

For getting the useful object information from infrared image and mining more detail of low light level (LLL) image, we propose a new fusion method based on segmentation and enhancement methods in the paper. First, using 2D maximum entropy method to segment the original infrared image for extracting infrared target, enhancing original LLL image by Zadeh transform for mining more detail information, on the basis of the segmented map to fuse the enhanced LLL image and original infrared image. Then, original infrared image, the enhanced LLL image and the first fused image are used to realize fusion in non-subsampled contourlet transform (NSCT) domain, we get the second fused image. By contrast of experiments, the fused image of the second fused method’s visual effect is better than other methods’ from the literature. Finally, Objective evaluation is used to evaluate the fused images’ quality, its results also show that the proposed method can pop target information, improve fused image’s resolution and contrast

A Novel Multi-focus Image Fusion Method Based on Non-negative Matrix Factorization

In order to efficiently extract the focused regions from the source images and improve the quality of the fused image, this paper presents a novel image fusion scheme with non-negative matrix factorization (NMF). The source images are fused by NMF to construct temporary fused image, whose region homogeneityis used to split the source images into regions.The focused regions are detected and integrated to construct the final fused image. Experimental results demonstrate that the proposedschemeis capable ofefficiently extracting the focused regions and significantly improving the fusion quality compared to other existing fusion methods,in terms of visualand quantitative evaluations

Multisensor Concealed Weapon Detection Using the Image Fusion Approach

Detection of concealed weapons is an increasingly important problem for both military and police since global terrorism and crime have grown as threats over the years. This work presents two image fusion algorithms, one at pixel level and another at feature level, for efficient concealed weapon detection application. Both the algorithms presented in this work are based on the double-density dual-tree complex wavelet transform (DDDTCWT). In the pixel level fusion scheme, the fusion of low frequency band coefficients is determined by the local contrast, while the high frequency band fusion rule is developed with consideration of both texture feature of the human visual system (HVS) and local energy basis. In the feature level fusion algorithm, features are exacted using Gaussian Mixture model (GMM) based multiscale segmentation approach and the fusion rules are developed based on region activity measurement. Experiment results demonstrate the robustness and efficiency of the proposed algorithms

Color and Dynamic Visual Signals Fusion

U tezi su predstavljene robusne, računski efikasne, metode za sjedinjavanje slika, video sekvenci i objektivne mere (algoritmi) za automatsku procenu uspešnosti sjedinjavanja slika i video sekvenci. Razvijeni algoritmi daju bolje rezultate nego postojeći i pri tome pogodni su za rad u realnom vremenu. U istraživanju uzet je u obzir i šum koji se javlja u realnom sistemu i predloženi su načini za njegovo prigušenje u samom procesu sjedinjavanja. Istraživanje je obuhvatilo i sprovođenje subjektivnih testova za procenu uspešnosti sjedinjavanja, kako bi se izvršilo podešavanje parametara metoda za sjedinjavanje i mera za procenu uspešnosti sjedinjavanja.The thesis presents robust, computer efficient, image and video sequencе fusion and objective measurements (algorithms) for automatically evaluating the success of image and video sequencе fusion. Developed algorithms provide better results than existing methods and they are suitable for real-time operation. The study also took into account the noise that occurs in the real systems, and proposed ways for its suppressing in the process of fusion. The survey also included the implementation of subjective tests to assess the success of the fusion, in order to make adjustments to the fusion parameters and measures for assessing the success of the fusion

Proceedings of the 7th Sound and Music Computing Conference

Proceedings of the SMC2010 - 7th Sound and Music Computing Conference, July 21st - July 24th 2010