Image Quantization with quantums Algorithm question

I came across a question and unable to find a feasible solution.

Image Quantization

Given a grayscale mage, each pixels color range from (0 to 255), compress the range of values to a given number of quantum values.

The goal is to do that with the minimum sum of costs needed, the cost of a pixel is defined as the absolute difference between its color and the closest quantum value for it.

Example

There are 3 rows 3 columns, image [[7,2,8], [8,2,3], [9,8 255]] quantums = 3 number of quantum values.The optimal quantum values are (2,8,255) Leading to the minimum sum of costs |7-8| + |2-2| + |8-8| + |8-8| + |2-2| + |3-2| + |9-8| + |8-8| + |255-255| = 1+0+0+0+0+1+1+0+0 = 3

Function description

Complete the solve function provided in the editor. This function takes the following 4 parameters and returns the minimum sum of costs.

n Represents the number of rows in the image

m Represents the number of columns in the image

image Represents the image

quantums Represents the number of quantum values.

Output: Print a single integer the minimum sum of costs/

Constraints: 

1<=n,m<=100
0<=image|i||j|<=255
1<=quantums<=256

Sample Input 1
3
3
7 2 8
8 2 3
9 8 255
10

Sample output 1
0

Explanation

The optimum quantum values are {0,1,2,3,4,5,7,8,9,255} Leading the minimum sum of costs |7-7| + |2-2| + |8-8| + |8-8| + |2-2| + |3-3| + |9-9| + |8-8| + |255-255| = 0+0+0+0+0+0+0+0+0 = 0

can anyone help me to reach the solution ?

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