Techniques for detecting small blobs in noisy images
I'd recommend looking at the state of the art using deep convolutional neural networks (CNNs) for object localization and detection. 

The difference is that a deep CNN architecture facilitates a data-driven approach, where the output of your CNN is a trainable classifier, that with more and different kinds of noisy/scaled/translated/permuted input data, can learn the feature maps that allow the CNN to generalize much better (say to different light &amp; noise conditions) than your hand-engineered features (morph filtering, laplace of gaussians, thresholding) used with a static threshold (0.001)

Start on github.