Point detection, Laplacian of Gaussian and High Boost Filtering

As with other posts, remove the commenting part in the below code to see the code working.
Pre-requisite You know imread, imshow and other functions in MATLAB.

clc;

%% Read Image
    %Reads the Image into an array for further processing
X = imread('build.tif');
    %X = rgb2gray(X);
   
%% Point detection
Y = imread('turbine.tif');
%Y1= bwareaopen(Y, 20);
% fplap = [1 1 1; 1 -8 1; 1 1 1]      %Laplacian at a point
fplap = [0 1 0; 1 -4 1; 0 1 0]      %Laplacian at a point
filtim = imfilter(Y,fplap,'symmetric', 'conv');

subplot(2,2,1)
imshow(Y);
title('Original');

subplot(2,2,2)
imshow(filtim);
title('Laplacian Point Filtered');

subplot(2,2,3)
imshow(Y-filtim);
title('Difference Image');

%% Gaussian Filtering of image
% fgauss = fspecial('gaussian',[25,25],4.0)
%         % 25X25 Gaussian filter with SD =25 is created.
% filtim = imfilter(X,fgauss,'symmetric', 'conv');
%         % Filter the image by convolution with the above designed filter.
%         % filtim now contains the gaussian filtered image.
%        
% subplot(2,2,1)
% imshow(X);
% title('Original');
%
% subplot(2,2,2)
% imshow(filtim);
% title('Gaussian Filtered');
%
% subplot(2,2,3)
% imshow(X-filtim);
% title('Difference Image');
%
% % flap1 = fspecial('laplacian', .2);
% % filtim1 = imfilter(filtim,flap1,'symmetric', 'conv');
%
% % fsobel = [-1 0 1; -2 0 2; -1 0 1]      %Grad in y
% fsobel = [-1 -2 -1; 0 0 0; 1 2 1]      %Grad in x
% % fsobel = [0 -1 -2; 1 0 -1; 2 1 0]        %45 degree
% filtim1 = imfilter(filtim,fsobel,'symmetric', 'conv');
%
% subplot(2,2,4)
% imshow(filtim1);
% title('LoG Image');

%% Spatial Filtering Smoothing <Weighted> &High Boost Filtering
%
% favg = [1/16 2/16 1/16; 2/16 4/16 2/16; 1/16 2/16 1/16]
% filtim = imfilter(X,favg,'symmetric', 'conv');
%
% subplot(2,2,1)
% imshow(X);
% title('Original');
%
% subplot(2,2,2)
% imshow(filtim);
% title('Weighted Filtering');
%
% subplot(2,2,3)
% imshow(X-filtim);
% title('Difference Image');
%
% subplot(2,2,4)
% imshow(X+0.2.*(X-filtim));
% title('High Boost Sharpened');

%%

Spatial Filtering etc

Assistance for Chapter 3 initial parts from Gonzalez and Woods,

Usage Help: Un-comment(Ctrl+T in Matlab) the required part of filtering and Run(F5) to understand the fun.
<Please keep a copy of a picture named as (1).jpg in the Matlab folder.

clc;

%% Read Image

X = imread('(1).jpg');

X = rgb2gray(X);

%% Histogram Equalisation of Image

% 

% figure;

% imhist(X);

% figure;

% histeq(X);

% figure;

% 

% imhist(histeq(X));

%% Gaussian Filtering of image

% fgauss = fspecial('gaussian',[3,3],1.0)

% filtim = imfilter(X,fgauss,'symmetric', 'conv');

% 

% subplot(1,2,1)

% imshow(X);

% subplot(1,2,2)

% imshow(filtim);

% figure

% imshow(X-filtim);

%% Spatial Filtering Smoothing <Weighted> &High Boost Filtering

% 

% favg = [1/16 2/16 1/16; 2/16 4/16 2/16; 1/16 2/16 1/16]

% filtim = imfilter(X,favg,'symmetric', 'conv');

% 

% subplot(2,2,1)

% imshow(X);

% title('Original');

% 

% subplot(2,2,2)

% imshow(filtim);

% title('Weighted Filtering');

% 

% subplot(2,2,3)

% imshow(X-filtim);

% title('Difference Image');

% 

% subplot(2,2,4)

% imshow(X+0.2.*(X-filtim));

% title('High Boost Sharpened');

% 

%% Median Filtering <Doubt, Anybody who knows please assist in this, right now the code is substituting %Median of first block for all the blocks>

% 

% filtim = imfilter(X,(double(median(median(X)))),'symmetric', 'conv');   %takes a single value for all the %matrices, how to make it floating

% 

% subplot(2,2,1)

% imshow(X);

% title('Original');

% 

% subplot(2,2,2)

% imshow(filtim);

% title('Median Filtering');

% 

% subplot(2,2,3)

% imshow(X-filtim);

% title('Difference Image');

%% Laplacian

% flap1 = fspecial('laplacian', .2);

% filtim1 = imfilter(X,flap1,'symmetric', 'conv');

% flap2 = -flap1;

% 

% subplot(2,2,1)

% imshow(X);

% title('Original');

% 

% subplot(2,2,2)

% imshow(filtim1);

% title('Laplacian Filtering - 1');

% 

% filtim2 = imfilter(X,flap2,'symmetric', 'conv');

% subplot(2,2,3)

% imshow(filtim2);

% title('Laplacian Filtering - 2');

% 

% subplot(2,2,4)

% imshow(X+(filtim1));

% title('Reconstructed after Laplacian');

%%