US 12,217,398 B1
Apparatus and method for single image dehazing considering haze type classification
Md Tanvir Islam, Riyadh (SA); Ik Hyun Lee, Riyadh (SA); Abdul Khader Jilani Saudagar, Riyadh (SA); Abdullah Altameem, Riyadh (SA); Mohammed Abaoud, Riyadh (SA); and Khan Muhammad, Riyadh (SA)
Assigned to IMAM MOHAMMAD IBN SAUD ISLAMIC UNIVERSITY, Riyadh (SA)
Filed by IMAM MOHAMMAD IBN SAUD ISLAMIC UNIVERSITY, Riyadh (SA)
Filed on May 8, 2024, as Appl. No. 18/658,673.
Int. Cl. G06T 5/60 (2024.01); G06T 5/73 (2024.01); G06V 10/70 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/94 (2022.01); G06V 20/50 (2022.01)
CPC G06T 5/60 (2024.01) [G06T 5/73 (2024.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/87 (2022.01); G06V 10/945 (2022.01); G06V 20/50 (2022.01); G06T 2207/10032 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20092 (2013.01); G06T 2207/30181 (2013.01); G06T 2207/30232 (2013.01); G06T 2207/30252 (2013.01)] 12 Claims
OG exemplary drawing
 
1. A method of dehazing an image having a haze condition and a haze-type class, comprising:
creating a plurality of image sets by splitting a plurality of ground truth images, wherein the plurality of image sets includes an outdoor image set, a street image set, a farmland image set, and a satellite image set;
transitioning each image set of the plurality of image sets by overlaying a synthetic haze condition to obtain a hazy dataset including a plurality of transitioned hazy images having a plurality of haze conditions, wherein the synthetic haze condition includes a haze intensity level;
training a plurality of haze-type classifier models and a plurality of specialized dehazer models with the hazy dataset;
determining a classifier model from the plurality of haze-type classifier models based on a classifier selector, wherein the classifier selector is a hybrid conditional classifier (HCC);
processing the image in accordance with a requirement of each haze-type classifier model of the plurality of haze-type classifier models to obtain a processed image;
determining the haze-type class of the image by the classifier model based on the processed image with the classifier model selected from the plurality of haze-type classifier models;
determining a dehazer from the plurality of specialized dehazer models based on the haze-type class; and
dehazing the image by removing the haze condition with the dehazer.