Hello Maulshree,
From the question above, I assume you want to know how the output image from the ‘demosaic’ function can be used as input for a CNN.
- The ‘demosaic’ function transforms a Bayer pattern encoded image into a true color RGB image, based on the specified sensor alignment. For further information on this function, refer to this documentation: https://www.mathworks.com/help/images/ref/demosaic.html .
RGB = demosaic(I,sensorAlignment)
- Once the images are in RGB format, they can be used as input for a CNN by creating an input layer. To do this, use the 'imageInputLayer' function. This function requires the image size as input and creates a layer that is compatible with CNN. For further information on this function, refer to this documentation: https://www.mathworks.com/help/deeplearning/ref/nnet.cnn.layer.imageinputlayer.html
layer = image3dInputLayer(inputImageSize)
To learn more about building a CNN, consult this documentation: https://www.mathworks.com/help/deeplearning/ug/introduction-to-convolutional-neural-networks.html .
