Effect of Channel Consideration on Auto Encoders for Color Image Compression using Deep Learning

In this paper, we have studied the effect of channels consideration on autoencoders for color image compression. The study is made in relation to RGB patch in an image and individual channel patches to know the effectiveness of what criteria is to be used while processing the image for compression. The study reveals that the RGB patch consideration in a color image is better than considering the channels individually. The chaotic (or scramble) image is given as input to autoencoder for compression and this helps to overcome the threat by the intruder and as well protection to data transmitted.