Hii Shanmugasundari Mariappan,
I understand that you want a clarity between the xcorr2 and conv2 function.
- Convolution: In convolution, the kernel (mask) is flipped both horizontally and vertically before before being applied to the mask or image. This flipping operation is equivalent to a 180-degree rotation of the kernel. MATLAB's 'conv2' function performs this flipped convolution.
- Cross-correlation: In cross-correlation, the mask is not rotated, and it is directly applied to the image. MATLAB's 'xcorr2' function calculates the cross-correlation between the mask and the image.
Also, I have mentioned the differnece between the two functions.
- 'conv2' function: The conv2 function in MATLAB performs convolution with a flipped (180-degree rotated) kernel. It follows the standard definition of convolution where the kernel is flipped before performing the convolution operation.
- 'xcorr2' function: The xcorr2 function in MATLAB performs cross-correlation, not convolution. Cross-correlation does not involve flipping the kernel. It directly applies the kernel to the input signal or image without any rotation.
To summarize the 'conv2' function performs convolution with a flipped kernel, while the 'xcorr2' function performs cross-correlation without any kernel rotation.
Kindly refer to the following links for better understanding:-
