  Quantum Information Theory promises to speed up computation so is observed in
real quantum computers as proved to its classical counterpart. This
revolutionizes every field linked directly or indirectly with computation.
Grover algorithm in quantum information gives quadratic speed up in
unstructured database search. With the availability of public online resources
for quantum computers like IBM, quantum image processing came into the picture
for making use of quantum computers in the image processing field. Our research
interest is to find all darker pixels in a 2x2 grayscale image using Grover's
algorithm. We studied it in two different ways. In the first method, I ran
Grover's algorithm on the python generated classical image. In the second
method, I converted a python-generated 2x2 image into a quantum image and then
ran Grover's algorithm to locate the darker pixels. As has been observed in
complexity analysis, Grover's unstructured search has the O(2^{n}) while as for
classical schemes O(2^{2n+2m}), where m and n denote the dimensions of the
image.
