Implementation of Haze Removal Algorithm to Enhance Low-Light Images Using Matlab

This example shows how to enhance low-light images using an algorithm suitable for FPGAs.

Haze removal or image dehazing is required in real-world weather conditions to obtain a fast and high-quality hazy free image which is used in various fields like satellite systems and aircraft systems.

Some of the wide important areas in which the haze removal methods used are air- crafts, remote sensing, intelligent transportation systems, underwater image processing, Object detection, outdoor surveillance, railway systems, aerial imagery, computational photography/vision applications, video analysis and recognition, image classification, military and defense surveillance system, etc. Example Code: % Import an RGB image captured in low light. A = imread('lowlight_21.jpg'); % Invert the image. AInv = imcomplement(A); % Apply the dehazing algorithm. BInv = imreducehaze(AInv,'ContrastEnhancement','none'); % Invert the results. B = imcomplement(BInv); %Display the original image and the enhanced images, side-by-side. montage({A,B}); click here to download the Matlab Livescript file: https://drive.google.com/file/d/1S8iBE42W0akwTQp2BksTsSd-NRb5MvV5/view?usp=sharing