Semantic-Color-Constancy-Using-CNN- Deep Learning projects-Matlab

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Semantic-Color-Constancy-Using-CNN- Deep Learning projects-Matlab

In this project,semantic color constancy using convolutional neural network.The goal of computational color constancy is to preserve the perceptive colors of objects under different lighting conditions by removing the effect of color casts caused by the scene's illumination.Deep learning based technique is used for image semantic segmentation.Semantic segmentation together with color and spatial information of input image to remove color casts.

The propsed method,we train a convolutional neural network model that learns to estimate the illuminant color and gamma correction parameters based on the semantic information of the given image.

Experimental results show that feeding the CNN with the semantic information leads to a significant improvement in the results.Illuminant estimation is also useful for 'auto white balance' an essential feature of the modern digital camera.

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