Enhanced image fusion using directional contrast rules in fuzzy transform domain

Abstract

In this paper a novel image fusion algorithm based on directional contrast in fuzzy transform (FTR) domain is proposed. Input images to be fused are first divided into several non-overlapping blocks. The components of these sub-blocks are fused using directional contrast based fuzzy fusion rule in FTR domain. The fused sub-blocks are then transformed into original size blocks using inverse-FTR. Further, these inverse transformed blocks are fused according to select maximum based fusion rule for reconstructing the final fused image. The proposed fusion algorithm is both visually and quantitatively compared with other standard and recent fusion algorithms. Experimental results demonstrate that the proposed method generates better results than the other methods.

Fuzzy enhanced image fusion using pixel intensity control

“…3a-d, respectively. We have shown the comparison in terms of qualitative measures among DWT-based image fusion [10], DWT with gamma enhancement [11], DWT with HE [12], adaptive HE [13], DC-FTR [14] and the proposed method. The performance of the proposed algorithm is demonstrated using subjective and objective image quality assessment.…”

“…So, total (N 3 /8)log 2 n butterflies are computed using fuzzy computation. For DC-FTR [14], the computational complexity includes discrete cosine fuzzy computations which are generalised for fuzzy computation, multiplication and additions as…”

“…Pixel-based contrast enhancement is one of the important image enhancement techniques in the spatial domain. There are various methods used in the literature, such as discrete wavelet transform (DWT)-based image fusion [10], DWT with gamma enhancement [11], DWT with histogram equalisation (HE) [12], contrast enhancement using gamma correction (GC) along with weighted distribution [13] and directional contrast-based enhancement using fuzzy transform enhancement [14] which is written as directional contrast-fuzzy transform (DC-FTR) throughout this paper.…”

“…It is based on non-linear transformation which maps the pixel intensity of the input image to the pixel intensity in the output image. Another novel image fusion algorithm based on the directional contrast in the fuzzy transform (FTR) domain is described in [14] where input images to be fused are first divided into several non-overlapping blocks. The components of these sub-blocks are fused using directional contrast based fuzzy fusion rules in the FTR domain.…”

Medical Images Enhanced by Using Fuzzy Logic Depending on Contrast Stretch Membership Function

“…Then only add the further steps to component V and finally marge all components including the improved components to getting the image of enhanced. Amita Nandal and Hamurabi Gamboa Rosales in [13] use fuzzy data to help deal with the inaccuracy of grey level values compared with conventional flat histogram-based approaches. This approach essentially prevents the presence of pictures blurred out.…”