Kernel estimation 6. Use the formula of 1D Gaussian function G(x)=21e22x2 to find coefficients of a 7. The size of a gaussian kernel is usually chosen to have values in the order of 2 or 3 sigmas, since after that the values of the function are almost zero. In the extreme parts of this kernel (when x is either 3 or 3 ) how many sigmas it corresponds to? Is the chosen size of 7 a good value? [10\%] 8. Approximate the obtained kernel as a fraction of integer numbers. Hint: use 64 as the denominator. [10\%] 9. Compute a 77 Gaussian kernel using the 1D estimated kernel you estimated in the previous exercise. Remember, this is a separable filter and can be obtained using matrix multiplication. [10\%] G=K71K17 10. In class we build a sharpen filter as the sum of original filter + detail. The detail part was built with the original function and a box filter. Create a new kernel for sharpening but this time uses a gaussian filter. [10\%]