Pixel & Feature Level Multiresolution Image Fusion Based On Fuzzy Logic

Multiview Fusion 3-d Echocardiography: Improving the Information and Quality of Real-Time 3-D Echocardiography

“…In fuzzy logic, the fusion rules usually determine the weight for contribution from each source image by looking either at intensity or feature values (Kayani et al 2007;Teng et al;Zhao et al 2005;Zhu and Yang 2008). Kayani et al (2007) proposed to use both wavelet transform and fuzzy logic for fusion where the fuzzy rules were applied on wavelet coefficients. In some cases, the image is segmented into important and unimportant regions before the fusion is performed using fuzzy logic (Kayani et al 2007).…”

“…Kayani et al (2007) proposed to use both wavelet transform and fuzzy logic for fusion where the fuzzy rules were applied on wavelet coefficients. In some cases, the image is segmented into important and unimportant regions before the fusion is performed using fuzzy logic (Kayani et al 2007). …”

A Survey on Image Fusion Requirements, Techniques, Evaluation Metrics, and Its Applications

“…Johnson Suthakar, J.Monica Esther M.E, etc.,(2014) [6] explained the aim of a image fusion process which is to produce a hybrid image with the best possible spatial data content while protecting the best spectral dataquality. Bushra N. Kayani and all (2007) [7] proposed scheme in which images are decomposed and subbands are combined with max coefficients of wavelet from two DWT coefficients. Codruta O. Ancuti, Cosmin Ancuti, Christophe De Vleeschouwer, Philippe Bekaert (2018) [8]presented an alternate method to improve underwater images and videos without any additional information than the original image, and also shown this approach is able to enhance underwater images with high accuracy and also recovers the important faded features and edges.…”