Table 2.

shows the diverse frequency domain based methods with their pros and cons as discussed by several authors

Fusion Techniques	Advantages	Disadvantages
Laplacian/Gausian pyramid [27, 28] Low pass pyramid ratio [29] Morphological pyramid [28] Gradient pyramid [30] Filter subtract decimate [30]	Provides better image quality of a representation for multi focus images	Provide almost same result. Number of breakdown levels affects the IF results
Discrete cosine transform (DCT) [38]	Decomposed images into series of waveform and used for real time applications	Low quality fused image
Discrete wavelet technique with Haar fusion [39]	Produced better quality of fused image with good SNR. Reduced the spectral distortion	Merged image has fewer spatial resolutions
Kekre’s wavelet transform fusion [43, 44]	Used for any size of images and its final fused result is more Infrmative	Computationally complex
Kekre’s hybrid wavelet based transform fusion [45, 46]	It gives better results	It cannot be used images integer power of two
Stationary wavelet transform (SWT) [35–37]	Give better result at level 2 of decomposition	Time consuming process
Stationary wavelet transform (SWT) and Curvelet Transform	Suitable for real time applications	Very time consuming process