A Significant Assessment of Image Fusion Techniques and its Performance Matrices
DOI:
https://doi.org/10.26438/ijcse/v6si8.6466Keywords:
mage fusion, Fused image, Discrete Wavelet Transform, Entropy, PSNRAbstract
The main aim of image fusion (IF) is to integrate complementary multisensor, multitemporal and/or multiview information into one new image containing information the quality of which cannot be achieved otherwise. The need of image fusion for high resolution on panchromatic and multispectral images or real world images for better vision. There are various methods of image fusion and some techniques of image fusion such as IHS, PCA, DWT, Laplacian pyramids, Gradient Pyramids, DCT, SF. Several digital image fusion algorithms have been developed in a number of applications. Image fusion extracts the information from several images of a given scene to obtain a final image which has more information for human visual perception and become more useful for additional vision processing. Various performance matrices that used for the evolution of image fusion are Entropy, Standard Deviation, Peak Signal to Noise Ratio (PSNR), and etc
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