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)] | 11 Claims |
1. A method of dehazing an image having a haze condition and a haze-type class obtained from a vehicle, comprising:
obtaining the image from an autonomous vehicle having a camera;
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.
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