[image enhancement] manual multiple exposure fusion amef image defogging based on MATLAB [including Matlab source code 1916]

One 、 Introduction to image enhancement technology

1 Image enhancement
Image enhancement is to some features of the image , Like the edge 、 outline 、 Emphasize or sharpen the contrast, etc , In order to display 、 Observe or further analyze and deal with . Through the specific processing of the image , Transforming the processed image into a visual image with better visual quality and effect for specific applications “ good ” Or more “ Useful ” Image .
Image enhancement is the most basic and commonly used image processing technology , It is often used in the preprocessing stage of other image processing .

（1） High pass smoothing 、 Low pass sharpening ; Smooth blur 、 Sharpen to highlight image details
（2） The filter also has bandpass 、 Band stop and other forms
（3） According to the noise （ Salt and pepper noise 、 Gaussian noise …） Different , Choose different filters
（4） Neighborhood has 4- Neighborhood 、 Diagonal neighborhood 、8- Neighborhood , The corresponding has adjacency , That is, spatially adjacent 、 Pixel grayscale is similar
（5） Image edge processing ： Ignore do not process 、 Add 、 Recycling
（6） At present, there is no image processing, and most of them are based on gray image

2 Polarization difference underwater fog principle
Polarization difference underwater fog principle

Two 、 Partial source code

function amef_demo


clc
clear all


% process a demo image
path = 'demo_images/';
% images shown in the paper
% im_name = [path, 'road_input.png']; % Fig. 10
% im_name = [path, '89.bmp']; % Fig. 7
im_name = [path, '91.jpg']; % Fig. 9
% im_name = [path, '98.bmp']; % Fig. 1
% im_name = [path, 'HazyDay.png']; % Fig. 8
% im_name = [path, '2.jpg']; % Fig. 6
% im_name = [path, 'mumbai.jpg']; % Fig. 13
% im_name = [path, 'landscape2-Tangkt.png']; % Fig. 11

% other examples
% im_name = [path, '2.jpg'];
% im_name = [path, '51.jpg'];
% im_name = [path, '88.jpg'];
% im_name = [path, '99.png'];
% im_name = [path, '100.png'];
% im_name = [path, 'fc7.jpg'];
% im_name = [path, 'IMG_4681_resize.jpg'];
% im_name = [path, 'Bu_Wf_D_L_040.jpg'];
% im_name = [path, '40.jpg'];
% im_name = [path, 'beijing3.png'];





I_hazy = imread(im_name);

% Increase clip_range to remove more haze - at the risk of overenhancement
clip_range = 0.010;

tic
amef_im = amef(im2double(I_hazy), clip_range);
time = toc;


[m, n, ~] = size(I_hazy);
disp(['Resolution: ', num2str(m), ' x ', num2str(n)])
disp(['Processing time: ', num2str(time)])

3、 ... and 、 Running results

Four 、matlab Edition and references

1 matlab edition
2014a

2 reference
[1] Cai Limei .MATLAB The image processing —— theory 、 Algorithm and example analysis [M]. tsinghua university press ,2020.
[2] Yang Dan , Zhao Haibin , Long Zhe .MATLAB Detailed explanation of image processing examples [M]. tsinghua university press ,2013.
[3] Zhou pin .MATLAB Image processing and graphical user interface design [M]. tsinghua university press ,2013.
[4] Liu Chenglong . Master MATLAB The image processing [M]. tsinghua university press ,2015.
[5] Li Lianzhi , Xing Chuan . Color enhancement algorithm of plane vision image based on homomorphic filtering [J]. Computer simulation . 2021,38(02)

3 remarks
This part of the introduction is taken from the Internet , For reference only , If infringement , Contact deletion