Paper Details

the goal of image fusion is to combine relevantinformation from two or more images of the same view in tosingle image. The result of image fusion is a new fused imagewhich is more suitable for human being and machinediscernment for further image-processing tasks likesegmentation, feature taking out and objects recognition. In thispaper the image fusion techniques described using the PCA, andwavelet family. Principal component analysis (PCA) is a wellknown scheme for feature extraction and dimension reduction.In DCT low frequency region of the image has large DCT coefficient. So it has very good energy compactness properties. InDWT image are di viding in low sub bands and high sub bandsare fused using various fusion methods. Finally, the output of thefused image is obtained by applying inverse wavelet transformon the fused coefficients of low sub bands and high sub bands.Where in curvelet it given smooth cured edge detection. Abovetechnique mainly done in two domain: spatial domain andtransform domain where it performed fusion at three differentprocessing levels which are pixel level, feature level and decisionlevel according to the stage at which the fusion takes place. Thisis depends on the required application

Dayagauri R. Padmani, Dr.K. R. Borisagar, “Theoretical Study of Image Fusion Techniques: A Review”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 2, Issue 14, pp. -, January 2015.