Image Fusion - New Advances

Image fusion is an important branch of information fusion, and it is also an important technology for image understanding and computer vision. The fusion process is to merging different images into one to get more accurate description for the scene. The text Image Fusion New Advances combines with many different disciplines, such as sensors, signal processing, image processing, computer and artificial intelligence. In first chapter, we discuss Shearlets and PCNN which are used to fuse images. A study on trous wavelet and image fusion has been proposed in second chapter. The objective evaluation index (OEI) for evaluation of night vision colorization techniques has been described in third chapter. Fourth chapter discusses on high-resolution and hyperspectral data fusion for classification. In fifth chapter, we deal with multi-frequency image fusion based on MIMO UWB OFDM synthetic aperture radar. The objective of sixth chapter is to develop a spatio-temporal image fusion model (STI-FM) for enhancing temporal resolution of Landsat-8 land surface temperature (LST) images by fusing LST images. Seventh chapter focuses on multi-sensor image fusion in remote sensing. The objective of eighth chapter is to present an overview of new advances in multi-sensor satellite image fusion. A novel fusion algorithm of multiple images based on fast integer lifting wavelet transform has been proposed in ninth chapter. In tenth chapter, we introduce color transfer techniques and some typical image fusion methods based on color transfer technique. Multifocus image fusion using biogeography-based optimization has been discussed in eleventh chapter. In twelfth chapter, we propose a region-based image fusion method to fuse spatially registered visible and infrared images while improving the contrast and preserving the significant features of input images. The effective multifocus image fusion based on HVS and BP neural network has been described in thirteenth chapter. Fourteenth chapter pres