Table 1.

shows the diverse spatial domain based methods with their pros and cons as per the literature review

Fusion Techniques	Advantages	Disadvantages
Averaging [14, 21] Minimum pixel value [14, 21] Simple block replacement [15] Maximum pixel value [14, 21] Max- min [15]	Simple, easy to recognize and implement	Decreases the image quality and reduces noise into final fused resultant image Produced blurred images. Not appropriate for real time applications
Weighted averaging [18]	Improves the detection reliability	Enhances the SNR
Principal component based analysis [22, 23]	Simple and more efficient, high spatial quality, lesser computational time	Resulted in color distortion and spectral degradation
Hue intensity saturation[21]	Efficient and simple. high sharpening ability and Fast processing	Color distortion
Brovey [14]	Extremely straightforward and more efficient method. Faster processing time. Gives Red–Green–Blue images with superior degree of contrast	Color distortion
Guided filtering[24]	It performs well in image smoothing or enhancement, flash or no-flash imaging, matting or feathering and joint upsampling	On the sparse inputs it is not directly applicable. It has a common drawback; it may have halos near some edges like other explicit filters