Convolution neural network with 11 million parameters unable to overfit on 100 image samples
You use a sigmoid activation in the last layer, which restricts your possible outputs to be between 0 and 1. This is typically used for binary classification, but it seems like you are not doing classification at all. If your image has values constrained to the range 0-1 then this is likely fine. Otherwise, this could be the source of your problem. 

I suggest removing the sigmoid activation in the final convolution and leaving it with no activation.